Adaptive Control of Four-Leg VSC Based DSTATCOM in Distribution System

NASA Astrophysics Data System (ADS)

Singh, Bhim; Arya, Sabha Raj

2014-01-01

This work discusses an experimental performance of a four-leg Distribution Static Compensator (DSTATCOM) using an adaptive filter based approach. It is used for estimation of reference supply currents through extracting the fundamental active power components of three-phase distorted load currents. This control algorithm is implemented on an assembled DSTATCOM for harmonics elimination, neutral current compensation and load balancing, under nonlinear loads. Experimental results are discussed, and it is noticed that DSTATCOM is effective solution to perform satisfactory performance under load dynamics.

Reduced Order Adaptive Controllers for Distributed Parameter Systems

DTIC Science & Technology

2005-09-01

pitch moment [J313. Neural Network adaptive output feedback control for intensive care unit sedation and intraop- erative anesthesia . Neural network...depth of anesthesia for noncardiac surgery [C3, J15]. These results present an extension of [C8, J9, J10]. Modelling and vibration control of...for Intensive Care Unit Sedation and Operating Room Hypnosis , Submitted to 6 Special Issue of SIAM Journal of Control and Optimization on Control

Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

NASA Astrophysics Data System (ADS)

Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

2018-03-01

The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

Cluster synchronization of community network with distributed time delays via impulsive control

NASA Astrophysics Data System (ADS)

Leng, Hui; Wu, Zhao-Yan

2016-11-01

Cluster synchronization is an important dynamical behavior in community networks and deserves further investigations. A community network with distributed time delays is investigated in this paper. For achieving cluster synchronization, an impulsive control scheme is introduced to design proper controllers and an adaptive strategy is adopted to make the impulsive controllers unified for different networks. Through taking advantage of the linear matrix inequality technique and constructing Lyapunov functions, some synchronization criteria with respect to the impulsive gains, instants, and system parameters without adaptive strategy are obtained and generalized to the adaptive case. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results. Project supported by the National Natural Science Foundation of China (Grant No. 61463022), the Natural Science Foundation of Jiangxi Province, China (Grant No. 20161BAB201021), and the Natural Science Foundation of Jiangxi Educational Committee, China (Grant No. GJJ14273).

Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture (Postprint)

DTIC Science & Technology

2007-09-18

TERMS turbine engine control, engine health management, FADEC , Universal FADEC , Distributed Controls, UF, UF Platform, common FADEC , Generic FADEC ...Modular FADEC , Adaptive Control 16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON (Monitor) a. REPORT Unclassified b. ABSTRACT...Eventually the Full Authority Digital Electronic Control ( FADEC ) became the norm. Presently, this control system architecture accounts for 15 to 20% of

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Application of free energy minimization to the design of adaptive multi-agent teams

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Pattipati, Krishna; Fouse, Adam; Serfaty, Daniel

2017-05-01

Many novel DoD missions, from disaster relief to cyber reconnaissance, require teams of humans and machines with diverse capabilities. Current solutions do not account for heterogeneity of agent capabilities, uncertainty of team knowledge, and dynamics of and dependencies between tasks and agent roles, resulting in brittle teams. Most importantly, the state-of-the-art team design solutions are either centralized, imposing role and relation assignment onto agents, or completely distributed, suitable for only homogeneous organizations such as swarms. Centralized design models can't provide insights for team's self-organization, i.e. adapting team structure over time in distributed collaborative manner by team members with diverse expertise and responsibilities. In this paper we present an information-theoretic formalization of team composition and structure adaptation using a minimization of variational free energy. The structure adaptation is obtained in an iterative distributed and collaborative manner without the need for centralized control. We show that our model is lightweight, predictive, and produces team structures that theoretically approximate an optimal policy for team adaptation. Our model also provides a unique coupling between the structure and action policy, and captures three essential processes of learning, perception, and control.

Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks.

PubMed

Li, Zhijun; Ge, Shuzhi Sam; Liu, Sibang

2014-08-01

This paper investigates optimal feet forces' distribution and control of quadruped robots under external disturbance forces. First, we formulate a constrained dynamics of quadruped robots and derive a reduced-order dynamical model of motion/force. Consider an external wrench on quadruped robots; the distribution of required forces and moments on the supporting legs of a quadruped robot is handled as a tip-point force distribution and used to equilibrate the external wrench. Then, a gradient neural network is adopted to deal with the optimized objective function formulated as to minimize this quadratic objective function subjected to linear equality and inequality constraints. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on an adaptive neural network to compensate for the perturbations in the environment and approximate feedforward force and impedance of the leg joints. The proposed control can confront the uncertainties including approximation error and external perturbation. The verification of the proposed control is conducted using a simulation.

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

PubMed

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

Adaptive Multi-Layer LMS Controller Design and Application to Active Vibration Suppression on a Truss and Proposed Impact Analysis Technique

DTIC Science & Technology

2001-06-01

Setup and Initiation ........................................................ 83 2. Simulation 1 (19 Hz, Y-axis of Node 18, Piezo #2...175 INITIAL DISTRIBUTION LIST ................................................................................... 187 ix...system for the sake of testing and simplicity. The Adaptive Multi-Layered LMS Controller was developed one piece at a time. After initial experimental

Adaptive sequential controller

DOEpatents

El-Sharkawi, Mohamed A.; Xing, Jian; Butler, Nicholas G.; Rodriguez, Alonso

1994-01-01

An adaptive sequential controller (50/50') for controlling a circuit breaker (52) or other switching device to substantially eliminate transients on a distribution line caused by closing and opening the circuit breaker. The device adaptively compensates for changes in the response time of the circuit breaker due to aging and environmental effects. A potential transformer (70) provides a reference signal corresponding to the zero crossing of the voltage waveform, and a phase shift comparator circuit (96) compares the reference signal to the time at which any transient was produced when the circuit breaker closed, producing a signal indicative of the adaptive adjustment that should be made. Similarly, in controlling the opening of the circuit breaker, a current transformer (88) provides a reference signal that is compared against the time at which any transient is detected when the circuit breaker last opened. An adaptive adjustment circuit (102) produces a compensation time that is appropriately modified to account for changes in the circuit breaker response, including the effect of ambient conditions and aging. When next opened or closed, the circuit breaker is activated at an appropriately compensated time, so that it closes when the voltage crosses zero and opens when the current crosses zero, minimizing any transients on the distribution line. Phase angle can be used to control the opening of the circuit breaker relative to the reference signal provided by the potential transformer.

Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

PubMed

Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

2017-01-01

Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

Service-oriented architecture for the ARGOS instrument control software

NASA Astrophysics Data System (ADS)

Borelli, J.; Barl, L.; Gässler, W.; Kulas, M.; Rabien, Sebastian

2012-09-01

The Advanced Rayleigh Guided ground layer Adaptive optic System, ARGOS, equips the Large Binocular Telescope (LBT) with a constellation of six rayleigh laser guide stars. By correcting atmospheric turbulence near the ground, the system is designed to increase the image quality of the multi-object spectrograph LUCIFER approximately by a factor of 3 over a field of 4 arc minute diameter. The control software has the critical task of orchestrating several devices, instruments, and high level services, including the already existing adaptive optic system and the telescope control software. All these components are widely distributed over the telescope, adding more complexity to the system design. The approach used by the ARGOS engineers is to write loosely coupled and distributed services under the control of different ownership systems, providing a uniform mechanism to offer, discover, interact and use these distributed capabilities. The control system counts with several finite state machines, vibration and flexure compensation loops, and safety mechanism, such as interlocks, aircraft, and satellite avoidance systems.

Method and apparatus for anti-islanding protection of distributed generations

DOEpatents

Ye, Zhihong; John, Vinod; Wang, Changyong; Garces, Luis Jose; Zhou, Rui; Li, Lei; Walling, Reigh Allen; Premerlani, William James; Sanza, Peter Claudius; Liu, Yan; Dame, Mark Edward

2006-03-21

An apparatus for anti-islanding protection of a distributed generation with respect to a feeder connected to an electrical grid is disclosed. The apparatus includes a sensor adapted to generate a voltage signal representative of an output voltage and/or a current signal representative of an output current at the distributed generation, and a controller responsive to the signals from the sensor. The controller is productive of a control signal directed to the distributed generation to drive an operating characteristic of the distributed generation out of a nominal range in response to the electrical grid being disconnected from the feeder.

Robust distributed control of spacecraft formation flying with adaptive network topology

NASA Astrophysics Data System (ADS)

Shasti, Behrouz; Alasty, Aria; Assadian, Nima

2017-07-01

In this study, the distributed six degree-of-freedom (6-DOF) coordinated control of spacecraft formation flying in low earth orbit (LEO) has been investigated. For this purpose, an accurate coupled translational and attitude relative dynamics model of the spacecraft with respect to the reference orbit (virtual leader) is presented by considering the most effective perturbation acceleration forces on LEO satellites, i.e. the second zonal harmonic and the atmospheric drag. Subsequently, the 6-DOF coordinated control of spacecraft in formation is studied. During the mission, the spacecraft communicate with each other through a switching network topology in which the weights of its graph Laplacian matrix change adaptively based on a distance-based connectivity function between neighboring agents. Because some of the dynamical system parameters such as spacecraft masses and moments of inertia may vary with time, an adaptive law is developed to estimate the parameter values during the mission. Furthermore, for the case that there is no knowledge of the unknown and time-varying parameters of the system, a robust controller has been developed. It is proved that the stability of the closed-loop system coupled with adaptation in network topology structure and optimality and robustness in control is guaranteed by the robust contraction analysis as an incremental stability method for multiple synchronized systems. The simulation results show the effectiveness of each control method in the presence of uncertainties and parameter variations. The adaptive and robust controllers show their superiority in reducing the state error integral as well as decreasing the control effort and settling time.

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-03-14

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

Distributed Adaptive Containment Control for a Class of Nonlinear Multiagent Systems With Input Quantization.

PubMed

Wang, Chenliang; Wen, Changyun; Hu, Qinglei; Wang, Wei; Zhang, Xiuyu

2018-06-01

This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.

Adaptive independent joint control of manipulators - Theory and experiment

NASA Technical Reports Server (NTRS)

Seraji, H.

1988-01-01

The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

System For Research On Multiple-Arm Robots

NASA Technical Reports Server (NTRS)

Backes, Paul G.; Hayati, Samad; Tso, Kam S.; Hayward, Vincent

1991-01-01

Kali system of computer programs and equipment provides environment for research on distributed programming and distributed control of coordinated-multiple-arm robots. Suitable for telerobotics research involving sensing and execution of low level tasks. Software and configuration of hardware designed flexible so system modified easily to test various concepts in control and programming of robots, including multiple-arm control, redundant-arm control, shared control, traded control, force control, force/position hybrid control, design and integration of sensors, teleoperation, task-space description and control, methods of adaptive control, control of flexible arms, and human factors.

Applications of active adaptive noise control to jet engines

NASA Technical Reports Server (NTRS)

Shoureshi, Rahmat; Brackney, Larry

1993-01-01

During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

Distributed Control Architecture for Gas Turbine Engine. Chapter 4

NASA Technical Reports Server (NTRS)

Culley, Dennis; Garg, Sanjay

2009-01-01

The transformation of engine control systems from centralized to distributed architecture is both necessary and enabling for future aeropropulsion applications. The continued growth of adaptive control applications and the trend to smaller, light weight cores is a counter influence on the weight and volume of control system hardware. A distributed engine control system using high temperature electronics and open systems communications will reverse the growing trend of control system weight ratio to total engine weight and also be a major factor in decreasing overall cost of ownership for aeropropulsion systems. The implementation of distributed engine control is not without significant challenges. There are the needs for high temperature electronics, development of simple, robust communications, and power supply for the on-board electronics.

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Comparison of Exposure Controls, Item Pool Characteristics, and Population Distributions for CAT Using the Partial Credit Model

ERIC Educational Resources Information Center

Lee, HwaYoung; Dodd, Barbara G.

2012-01-01

This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability…

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

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

Adaption of the LHC cold mass cooling system to the requirements of the Future Circular Collider (FCC)

NASA Astrophysics Data System (ADS)

Kotnig, C.; Tavian, L.; Brenn, G.

2017-12-01

The cooling of the superconducting magnet cold masses with superfluid helium (He II) is a well-established concept successfully in operation for years in the LHC. Consequently, its application for the cooling of FCC magnets is an obvious option. The 12-kW heat loads distributed over 10-km long sectors not only require an adaption of the magnet bayonet heat exchangers but also present new challenges to the cryogenic plants, the distribution system and the control strategy. This paper recalls the basic LHC cooling concept with superfluid helium and defines the main parameters for the adaption to the FCC requirements. Pressure drop and hydrostatic head are developed in the distribution and pumping systems; their impact on the magnet temperature profile and the corresponding cooling efficiency is presented and compared for different distribution and pumping schemes.

Adaptive architectures for resilient control of networked multiagent systems in the presence of misbehaving agents

NASA Astrophysics Data System (ADS)

Torre, Gerardo De La; Yucelen, Tansel

2018-03-01

Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise components can easily result in system instability and prohibit the accomplishment of system-level objectives. In this paper, we study resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e. agents that are subject to exogenous disturbances that represent a class of adverse conditions. In particular, a distributed adaptive control architecture is presented for directed and time-varying graph topologies to retrieve a desired networked multiagent system behaviour. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we show that the considered class of adverse conditions can be mitigated by the proposed adaptive control approach that utilises a local state emulator - even if all agents are misbehaving. Illustrative numerical examples are provided to demonstrate the theoretical findings.

Distributed Adaptive Neural Control for Stochastic Nonlinear Multiagent Systems.

PubMed

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

2016-11-14

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

Control allocation-based adaptive control for greenhouse climate

NASA Astrophysics Data System (ADS)

Su, Yuanping; Xu, Lihong; Goodman, Erik D.

2018-04-01

This paper presents an adaptive approach to greenhouse climate control, as part of an integrated control and management system for greenhouse production. In this approach, an adaptive control algorithm is first derived to guarantee the asymptotic convergence of the closed system with uncertainty, then using that control algorithm, a controller is designed to satisfy the demands for heat and mass fluxes to maintain inside temperature, humidity and CO2 concentration at their desired values. Instead of applying the original adaptive control inputs directly, second, a control allocation technique is applied to distribute the demands of the heat and mass fluxes to the actuators by minimising tracking errors and energy consumption. To find an energy-saving solution, both single-objective optimisation (SOO) and multiobjective optimisation (MOO) in the control allocation structure are considered. The advantage of the proposed approach is that it does not require any a priori knowledge of the uncertainty bounds, and the simulation results illustrate the effectiveness of the proposed control scheme. It also indicates that MOO saves more energy in the control process.

Adaptive kanban control mechanism for a single-stage hybrid system

NASA Astrophysics Data System (ADS)

Korugan, Aybek; Gupta, Surendra M.

2002-02-01

In this paper, we consider a hybrid manufacturing system with two discrete production lines. Here the output of either production line can satisfy the demand for the same type of product without any penalties. The interarrival times for demand occurrences and service completions are exponentially distributed i.i.d. variables. In order to control this type of manufacturing system we suggest a single stage pull type control mechanism with adaptive kanbans and state independent routing of the production information.

Aging Affects Adaptation to Sound-Level Statistics in Human Auditory Cortex.

PubMed

Herrmann, Björn; Maess, Burkhard; Johnsrude, Ingrid S

2018-02-21

Optimal perception requires efficient and adaptive neural processing of sensory input. Neurons in nonhuman mammals adapt to the statistical properties of acoustic feature distributions such that they become sensitive to sounds that are most likely to occur in the environment. However, whether human auditory responses adapt to stimulus statistical distributions and how aging affects adaptation to stimulus statistics is unknown. We used MEG to study how exposure to different distributions of sound levels affects adaptation in auditory cortex of younger (mean: 25 years; n = 19) and older (mean: 64 years; n = 20) adults (male and female). Participants passively listened to two sound-level distributions with different modes (either 15 or 45 dB sensation level). In a control block with long interstimulus intervals, allowing neural populations to recover from adaptation, neural response magnitudes were similar between younger and older adults. Critically, both age groups demonstrated adaptation to sound-level stimulus statistics, but adaptation was altered for older compared with younger people: in the older group, neural responses continued to be sensitive to sound level under conditions in which responses were fully adapted in the younger group. The lack of full adaptation to the statistics of the sensory environment may be a physiological mechanism underlying the known difficulty that older adults have with filtering out irrelevant sensory information. SIGNIFICANCE STATEMENT Behavior requires efficient processing of acoustic stimulation. Animal work suggests that neurons accomplish efficient processing by adjusting their response sensitivity depending on statistical properties of the acoustic environment. Little is known about the extent to which this adaptation to stimulus statistics generalizes to humans, particularly to older humans. We used MEG to investigate how aging influences adaptation to sound-level statistics. Listeners were presented with sounds drawn from sound-level distributions with different modes (15 vs 45 dB). Auditory cortex neurons adapted to sound-level statistics in younger and older adults, but adaptation was incomplete in older people. The data suggest that the aging auditory system does not fully capitalize on the statistics available in sound environments to tune the perceptual system dynamically. Copyright © 2018 the authors 0270-6474/18/381989-11$15.00/0.

Aircraft adaptive learning control

NASA Technical Reports Server (NTRS)

Lee, P. S. T.; Vanlandingham, H. F.

1979-01-01

The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

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

Kurt Derr; Milos Manic

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersionmore » of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.« less

Adaptive, full-spectrum solar energy system

DOEpatents

Muhs, Jeffrey D.; Earl, Dennis D.

2003-08-05

An adaptive full spectrum solar energy system having at least one hybrid solar concentrator, at least one hybrid luminaire, at least one hybrid photobioreactor, and a light distribution system operably connected to each hybrid solar concentrator, each hybrid luminaire, and each hybrid photobioreactor. A lighting control system operates each component.

An experimental study of an adaptive-wall wind tunnel

NASA Technical Reports Server (NTRS)

Celik, Zeki; Roberts, Leonard

1988-01-01

A series of adaptive wall ventilated wind tunnel experiments was carried out to demonstrate the feasibility of using the side wall pressure distribution as the flow variable for the assessment of compatibility with free air conditions. Iterative and one step convergence methods were applied using the streamwise velocity component, the side wall pressure distribution and the normal velocity component in order to investigate their relative merits. The advantage of using the side wall pressure as the flow variable is to reduce the data taking time which is one the major contributors to the total testing time. In ventilated adaptive wall wind tunnel testing, side wall pressure measurements require simple instrumentation as opposed to the Laser Doppler Velocimetry used to measure the velocity components. In ventilated adaptive wall tunnel testing, influence coefficients are required to determine the pressure corrections in the plenum compartment. Experiments were carried out to evaluate the influence coefficients from side wall pressure distributions, and from streamwise and normal velocity distributions at two control levels. Velocity measurements were made using a two component Laser Doppler Velocimeter system.

Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

NASA Technical Reports Server (NTRS)

Tesar, Delbert; Tosunoglu, Sabri; Lin, Shyng-Her

1990-01-01

Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied.

Distribution of tubulin, kinesin, and dynein in light- and dark-adapted octopus retinas.

PubMed

Martinez, J M; Elfarissi, H; De Velasco, B; Ochoa, G H; Miller, A M; Clark, Y M; Matsumoto, B; Robles, L J

2000-01-01

Cephalopod retinas exhibit several responses to light and dark adaptation, including rhabdom size changes, photopigment movements, and pigment granule migration. Light- and dark-directed rearrangements of microfilament and microtubule cytoskeletal transport pathways could drive these changes. Recently, we localized actin-binding proteins in light-/dark-adapted octopus rhabdoms and suggested that actin cytoskeletal rearrangements bring about the formation and degradation of rhabdomere microvilli subsets. To determine if the microtubule cytoskeleton and associated motor proteins control the other light/dark changes, we used immunoblotting and immunocytochemical procedures to map the distribution of tubulin, kinesin, and dynein in dorsal and ventral halves of light- and dark-adapted octopus retinas. Immunoblots detected alpha- and beta-tubulin, dynein intermediate chain, and kinesin heavy chain in extracts of whole retinas. Epifluorescence and confocal microscopy showed that the tubulin proteins were distributed throughout the retina with more immunoreactivity in retinas exposed to light. Kinesin localization was heavy in the pigment layer of light- and dark-adapted ventral retinas but was less prominent in the dorsal region. Dynein distribution also varied in dorsal and ventral retinas with more immunoreactivity in light- and dark-adapted ventral retinas and confocal microscopy emphasized the granular nature of this labeling. We suggest that light may regulate the distribution of microtubule cytoskeletal proteins in the octopus retina and that position, dorsal versus ventral, also influences the distribution of motor proteins. The microtubule cytoskeleton is most likely involved in pigment granule migration in the light and dark and with the movement of transport vesicles from the photoreceptor inner segments to the rhabdoms.

Adaptive Fuzzy Hysteresis Band Current Controller for Four-Wire Shunt Active Filter

NASA Astrophysics Data System (ADS)

Hamoudi, F.; Chaghi, A.; Amimeur, H.; Merabet, E.

2008-06-01

This paper presents an adaptive fuzzy hysteresis band current controller for four-wire shunt active power filters to eliminate harmonics and to compensate reactive power in distribution systems in order to keep currents at the point of common coupling sinusoidal and in phase with the corresponding voltage and the cancel neutral current. The conventional hysteresis band known for its robustness and its advantage in current controlled applications is adapted with a fuzzy logic controller to change the bandwidth according to the operating point in order to keep the frequency modulation at tolerable limits. The algorithm used to identify the reference currents is based on the synchronous reference frame theory (dqγ). Finally, simulation results using Matlab/Simulink are given to validate the proposed control.

Probabilistic co-adaptive brain-computer interfacing

NASA Astrophysics Data System (ADS)

Bryan, Matthew J.; Martin, Stefan A.; Cheung, Willy; Rao, Rajesh P. N.

2013-12-01

Objective. Brain-computer interfaces (BCIs) are confronted with two fundamental challenges: (a) the uncertainty associated with decoding noisy brain signals, and (b) the need for co-adaptation between the brain and the interface so as to cooperatively achieve a common goal in a task. We seek to mitigate these challenges. Approach. We introduce a new approach to brain-computer interfacing based on partially observable Markov decision processes (POMDPs). POMDPs provide a principled approach to handling uncertainty and achieving co-adaptation in the following manner: (1) Bayesian inference is used to compute posterior probability distributions (‘beliefs’) over brain and environment state, and (2) actions are selected based on entire belief distributions in order to maximize total expected reward; by employing methods from reinforcement learning, the POMDP’s reward function can be updated over time to allow for co-adaptive behaviour. Main results. We illustrate our approach using a simple non-invasive BCI which optimizes the speed-accuracy trade-off for individual subjects based on the signal-to-noise characteristics of their brain signals. We additionally demonstrate that the POMDP BCI can automatically detect changes in the user’s control strategy and can co-adaptively switch control strategies on-the-fly to maximize expected reward. Significance. Our results suggest that the framework of POMDPs offers a promising approach for designing BCIs that can handle uncertainty in neural signals and co-adapt with the user on an ongoing basis. The fact that the POMDP BCI maintains a probability distribution over the user’s brain state allows a much more powerful form of decision making than traditional BCI approaches, which have typically been based on the output of classifiers or regression techniques. Furthermore, the co-adaptation of the system allows the BCI to make online improvements to its behaviour, adjusting itself automatically to the user’s changing circumstances.

Rendezvous with connectivity preservation for multi-robot systems with an unknown leader

NASA Astrophysics Data System (ADS)

Dong, Yi

2018-02-01

This paper studies the leader-following rendezvous problem with connectivity preservation for multi-agent systems composed of uncertain multi-robot systems subject to external disturbances and an unknown leader, both of which are generated by a so-called exosystem with parametric uncertainty. By combining internal model design, potential function technique and adaptive control, two distributed control strategies are proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances. It is also worth to mention that the uncertain parameters in the multi-robot systems and exosystem are further allowed to belong to unknown and unbounded sets when applying the second fully distributed control law containing a dynamic gain inspired by high-gain adaptive control or self-tuning regulator.

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

PubMed

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

An adaptive grid scheme using the boundary element method

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

Munipalli, R.; Anderson, D.A.

1996-09-01

A technique to solve the Poisson grid generation equations by Green`s function related methods has been proposed, with the source terms being purely position dependent. The use of distributed singularities in the flow domain coupled with the boundary element method (BEM) formulation is presented in this paper as a natural extension of the Green`s function method. This scheme greatly simplifies the adaption process. The BEM reduces the dimensionality of the given problem by one. Internal grid-point placement can be achieved for a given boundary distribution by adding continuous and discrete source terms in the BEM formulation. A distribution of vortexmore » doublets is suggested as a means of controlling grid-point placement and grid-line orientation. Examples for sample adaption problems are presented and discussed. 15 refs., 20 figs.« less

Modeling, Control, and Estimation of Flexible, Aerodynamic Structures

NASA Astrophysics Data System (ADS)

Ray, Cody W.

Engineers have long been inspired by nature’s flyers. Such animals navigate complex environments gracefully and efficiently by using a variety of evolutionary adaptations for high-performance flight. Biologists have discovered a variety of sensory adaptations that provide flow state feedback and allow flying animals to feel their way through flight. A specialized skeletal wing structure and plethora of robust, adaptable sensory systems together allow nature’s flyers to adapt to myriad flight conditions and regimes. In this work, motivated by biology and the successes of bio-inspired, engineered aerial vehicles, linear quadratic control of a flexible, morphing wing design is investigated, helping to pave the way for truly autonomous, mission-adaptive craft. The proposed control algorithm is demonstrated to morph a wing into desired positions. Furthermore, motivated specifically by the sensory adaptations organisms possess, this work transitions to an investigation of aircraft wing load identification using structural response as measured by distributed sensors. A novel, recursive estimation algorithm is utilized to recursively solve the inverse problem of load identification, providing both wing structural and aerodynamic states for use in a feedback control, mission-adaptive framework. The recursive load identification algorithm is demonstrated to provide accurate load estimate in both simulation and experiment.

Development of Variable Camber Continuous Trailing Edge Flap for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Kaul, Upender; Lebofsky, Sonia; Ting, Eric; Chaparro, Daniel; Urnes, James

2015-01-01

This paper summarizes the recent development of an adaptive aeroelastic wing shaping control technology called variable camber continuous trailing edge flap (VCCTEF). As wing flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. The initial VCCTEF concept was developed in 2010 by NASA under a NASA Innovation Fund study entitled "Elastically Shaped Future Air Vehicle Concept," which showed that highly flexible wing aerodynamic surfaces can be elastically shaped in-flight by active control of wing twist and bending deflection in order to optimize the spanwise lift distribution for drag reduction. A collaboration between NASA and Boeing Research & Technology was subsequently funded by NASA from 2012 to 2014 to further develop the VCCTEF concept. This paper summarizes some of the key research areas conducted by NASA during the collaboration with Boeing Research and Technology. These research areas include VCCTEF design concepts, aerodynamic analysis of VCCTEF camber shapes, aerodynamic optimization of lift distribution for drag minimization, wind tunnel test results for cruise and high-lift configurations, flutter analysis and suppression control of flexible wing aircraft, and multi-objective flight control for adaptive aeroelastic wing shaping control.

Distributed cerebellar plasticity implements adaptable gain control in a manipulation task: a closed-loop robotic simulation

PubMed Central

Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo

2013-01-01

Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario. PMID:24130518

Adaptation and visual salience

PubMed Central

McDermott, Kyle C.; Malkoc, Gokhan; Mulligan, Jeffrey B.; Webster, Michael A.

2011-01-01

We examined how the salience of color is affected by adaptation to different color distributions. Observers searched for a color target on a dense background of distractors varying along different directions in color space. Prior adaptation to the backgrounds enhanced search on the same background while adaptation to orthogonal background directions slowed detection. Advantages of adaptation were seen for both contrast adaptation (to different color axes) and chromatic adaptation (to different mean chromaticities). Control experiments, including analyses of eye movements during the search, suggest that these aftereffects are unlikely to reflect simple learning or changes in search strategies on familiar backgrounds, and instead result from how adaptation alters the relative salience of the target and background colors. Comparable effects were observed along different axes in the chromatic plane or for axes defined by different combinations of luminance and chromatic contrast, consistent with visual search and adaptation mediated by multiple color mechanisms. Similar effects also occurred for color distributions characteristic of natural environments with strongly selective color gamuts. Our results are consistent with the hypothesis that adaptation may play an important functional role in highlighting the salience of novel stimuli by discounting ambient properties of the visual environment. PMID:21106682

Stable Direct Adaptive Control of Linear Infinite-dimensional Systems Using a Command Generator Tracker Approach

NASA Technical Reports Server (NTRS)

Balas, M. J.; Kaufman, H.; Wen, J.

1985-01-01

A command generator tracker approach to model following contol of linear distributed parameter systems (DPS) whose dynamics are described on infinite dimensional Hilbert spaces is presented. This method generates finite dimensional controllers capable of exponentially stable tracking of the reference trajectories when certain ideal trajectories are known to exist for the open loop DPS; we present conditions for the existence of these ideal trajectories. An adaptive version of this type of controller is also presented and shown to achieve (in some cases, asymptotically) stable finite dimensional control of the infinite dimensional DPS.

The Effect of Aging on the Dynamics of Reactive and Proactive Cognitive Control of Response Interference

PubMed Central

Xiang, Ling; Zhang, Baoqiang; Wang, Baoxi; Jiang, Jun; Zhang, Fenghua; Hu, Zhujing

2016-01-01

A prime-target interference task was used to investigate the effects of cognitive aging on reactive and proactive control after eliminating frequency confounds and feature repetitions from the cognitive control measures. We used distributional analyses to explore the dynamics of the two control functions by distinguishing the strength of incorrect response capture and the efficiency of suppression control. For reactive control, within-trial conflict control and between-trial conflict adaption were analyzed. The statistical analysis showed that there were no reliable between-trial conflict adaption effects for either young or older adults. For within-trial conflict control, the results revealed that older adults showed larger interference effects on mean RT and mean accuracy. Distributional analyses showed that the decline mainly stemmed from inefficient suppression rather than from stronger incorrect responses. For proactive control, older adults showed comparable proactive conflict resolution to young adults on mean RT and mean accuracy. Distributional analyses showed that older adults were as effective as younger adults in adjusting their responses based on congruency proportion information to minimize automatic response capture and actively suppress the direct response activation. The results suggest that older adults were less proficient at suppressing interference after conflict was detected but can anticipate and prevent inference in response to congruency proportion manipulation. These results challenge earlier views that older adults have selective deficits in proactive control but intact reactive control. PMID:27847482

The Effect of Aging on the Dynamics of Reactive and Proactive Cognitive Control of Response Interference.

PubMed

Xiang, Ling; Zhang, Baoqiang; Wang, Baoxi; Jiang, Jun; Zhang, Fenghua; Hu, Zhujing

2016-01-01

A prime-target interference task was used to investigate the effects of cognitive aging on reactive and proactive control after eliminating frequency confounds and feature repetitions from the cognitive control measures. We used distributional analyses to explore the dynamics of the two control functions by distinguishing the strength of incorrect response capture and the efficiency of suppression control. For reactive control, within-trial conflict control and between-trial conflict adaption were analyzed. The statistical analysis showed that there were no reliable between-trial conflict adaption effects for either young or older adults. For within-trial conflict control, the results revealed that older adults showed larger interference effects on mean RT and mean accuracy. Distributional analyses showed that the decline mainly stemmed from inefficient suppression rather than from stronger incorrect responses. For proactive control, older adults showed comparable proactive conflict resolution to young adults on mean RT and mean accuracy. Distributional analyses showed that older adults were as effective as younger adults in adjusting their responses based on congruency proportion information to minimize automatic response capture and actively suppress the direct response activation. The results suggest that older adults were less proficient at suppressing interference after conflict was detected but can anticipate and prevent inference in response to congruency proportion manipulation. These results challenge earlier views that older adults have selective deficits in proactive control but intact reactive control.

Distributed cooperative H∞ optimal tracking control of MIMO nonlinear multi-agent systems in strict-feedback form via adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Luy, N. T.

2018-04-01

The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.

A biologically based model for the integration of sensory-motor contingencies in rules and plans: a prefrontal cortex based extension of the Distributed Adaptive Control architecture.

PubMed

Duff, Armin; Fibla, Marti Sanchez; Verschure, Paul F M J

2011-06-30

Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents. Copyright © 2010 Elsevier Inc. All rights reserved.

Discrete-time entropy formulation of optimal and adaptive control problems

NASA Technical Reports Server (NTRS)

Tsai, Yweting A.; Casiello, Francisco A.; Loparo, Kenneth A.

1992-01-01

The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

An integration time adaptive control method for atmospheric composition detection of occultation

NASA Astrophysics Data System (ADS)

Ding, Lin; Hou, Shuai; Yu, Fei; Liu, Cheng; Li, Chao; Zhe, Lin

2018-01-01

When sun is used as the light source for atmospheric composition detection, it is necessary to image sun for accurate identification and stable tracking. In the course of 180 second of the occultation, the magnitude of sun light intensity through the atmosphere changes greatly. It is nearly 1100 times illumination change between the maximum atmospheric and the minimum atmospheric. And the process of light change is so severe that 2.9 times per second of light change can be reached. Therefore, it is difficult to control the integration time of sun image camera. In this paper, a novel adaptive integration time control method for occultation is presented. In this method, with the distribution of gray value in the image as the reference variable, and the concepts of speed integral PID control, the integration time adaptive control problem of high frequency imaging. The large dynamic range integration time automatic control in the occultation can be achieved.

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems. Multi-University Research Initiative on High-Confidence Design for Distributed Embedded Systems

DTIC Science & Technology

2009-01-01

controllers (currently using the Robostix+Gumstix pair ). The interface between the plant simulator and the controller is ‘hard real-time’, and the xPC box... simulation ) on aerobatic maneuver design for the STARMAC quadrotor helicopter testbed. In related work, we have developed a new optimization scheme...for scheduling hybrid systems, and have demonstrated the results on an autonomous car simulation testbed. We are focusing efforts this summer for

The structure, distribution, and biomass of the world's forests

Treesearch

Yude Pan; Richard A. Birdsey; Oliver L. Phillips; Robert B. Jackson

2013-01-01

Forests are the dominant terrestrial ecosystem on Earth. We review the environmental factors controlling their structure and global distribution and evaluate their current and future trajectory. Adaptations of trees to climate and resource gradients, coupled with disturbances and forest dynamics, create complex geographical patterns in forest assemblages and structures...

Realizing Autonomy via Intelligent Hybrid Control: Adaptable Autonomy for Achieving UxV RSTA Team Decision Superiority (also known as Intelligent Multi-UxV Planner with Adaptive Collaborative/Control Technologies (IMPACT))

DTIC Science & Technology

2018-01-30

algorithms. Due to this, Fusion was built with the goal of extensibility throughout the architecture. The Fusion infrastructure enables software...DISTRIBUTION STATEMENT A: Approved for public release. Cleared, 88PA, Case# 2018-0820. b. Trigger a Highly Mobile ...modes were developed in IMPACT (i.e., normal full coverage patrol (NFCP) and highly mobile (HM)). In both NFCP and HM, all UxVs patrol their assigned

Applications of Neural Networks to Adaptive Control

DTIC Science & Technology

1989-12-01

DTIC ;-E py 00 NAVAL POSTGRADUATE SCHOOL Monterey, California I.$ RDTIC IELECTE fl THESIS BEG7V°U APPLICATIONS OF NEURAL NETWORKS TO ADAPTIVE CONTROL...MONITORING ORGANIZATION Naval Postgraduate School (10 applicable) Naval Postgraduate School 6< ADDRESS (C~tV Start, and ZIPCode) 7b ADDRESS(City. Stott...eshausted SICURIIY CLAS$SItATO’. -r’, T..i5 PAGE~ All oth~er edit,ons art obsolete U11C1ASS 11- I’ Approved for Public release; distribution unlimited

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

High level continuity for coordinate generation with precise controls

NASA Technical Reports Server (NTRS)

Eiseman, P. R.

1982-01-01

Coordinate generation techniques with precise local controls have been derived and analyzed for continuity requirements up to both the first and second derivatives, and have been projected to higher level continuity requirements from the established pattern. The desired local control precision was obtained when a family of coordinate surfaces could be uniformly distributed without a consequent creation of flat spots on the coordinate curves transverse to the family. Relative to the uniform distribution, the family could be redistributed from an a priori distribution function or from a solution adaptive approach, both without distortion from the underlying transformation which may be independently chosen to fit a nontrivial geometry and topology.

Distributed sensor architecture for intelligent control that supports quality of control and quality of service.

PubMed

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-02-25

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

Distributed Sensor Architecture for Intelligent Control that Supports Quality of Control and Quality of Service

PubMed Central

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-01-01

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems. PMID:25723145

Bayesian nonparametric adaptive control using Gaussian processes.

PubMed

Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

2015-03-01

Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

Automated information and control complex of hydro-gas endogenous mine processes

NASA Astrophysics Data System (ADS)

Davkaev, K. S.; Lyakhovets, M. V.; Gulevich, T. M.; Zolin, K. A.

2017-09-01

The automated information and control complex designed to prevent accidents, related to aerological situation in the underground workings, accounting of the received and handed over individual devices, transmission and display of measurement data, and the formation of preemptive solutions is considered. Examples for the automated workplace of an airgas control operator by individual means are given. The statistical characteristics of field data characterizing the aerological situation in the mine are obtained. The conducted studies of statistical characteristics confirm the feasibility of creating a subsystem of controlled gas distribution with an adaptive arrangement of points for gas control. The adaptive (multivariant) algorithm for processing measuring information of continuous multidimensional quantities and influencing factors has been developed.

Software Testbed for Developing and Evaluating Integrated Autonomous Systems

DTIC Science & Technology

2015-03-01

EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to...using the Internet Communications Engine ( ICE ), an object-oriented toolkit for building distributed applications. TABLE OF CONTENTS 1...ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA???s EUROPA planning system for plan generation. The adaptive

Revisiting control establishments for emerging energy hubs

NASA Astrophysics Data System (ADS)

Nasirian, Vahidreza

Emerging small-scale energy systems, i.e., microgrids and smartgrids, rely on centralized controllers for voltage regulation, load sharing, and economic dispatch. However, the central controller is a single-point-of-failure in such a design as either the controller or attached communication links failure can render the entire system inoperable. This work seeks for alternative distributed control structures to improve system reliability and help to the scalability of the system. A cooperative distributed controller is proposed that uses a noise-resilient voltage estimator and handles global voltage regulation and load sharing across a DC microgrid. Distributed adaptive droop control is also investigated as an alternative solution. A droop-free distributed control is offered to handle voltage/frequency regulation and load sharing in AC systems. This solution does not require frequency measurement and, thus, features a fast frequency regulation. Distributed economic dispatch is also studied, where a distributed protocol is designed that controls generation units to merge their incremental costs into a consensus and, thus, push the entire system to generate with the minimum cost. Experimental verifications and Hardware-in-the-Loop (HIL) simulations are used to study efficacy of the proposed control protocols.

Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

NASA Astrophysics Data System (ADS)

Stockhause, M.; Höck, H.; Toussaint, F.; Lautenschlager, M.

2012-08-01

The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

Influence of Lumbar Muscle Fatigue on Trunk Adaptations during Sudden External Perturbations

PubMed Central

Abboud, Jacques; Nougarou, François; Lardon, Arnaud; Dugas, Claude; Descarreaux, Martin

2016-01-01

Introduction: When the spine is subjected to perturbations, neuromuscular responses such as reflex muscle contractions contribute to the overall balance control and spinal stabilization mechanisms. These responses are influenced by muscle fatigue, which has been shown to trigger changes in muscle recruitment patterns. Neuromuscular adaptations, e.g., attenuation of reflex activation and/or postural oscillations following repeated unexpected external perturbations, have also been described. However, the characterization of these adaptations still remains unclear. Using high-density electromyography (EMG) may help understand how the nervous system chooses to deal with an unknown perturbation in different physiological and/or mechanical perturbation environments. Aim: To characterize trunk neuromuscular adaptations following repeated sudden external perturbations after a back muscle fatigue task using high-density EMG. Methods: Twenty-five healthy participants experienced a series of 15 sudden external perturbations before and after back muscle fatigue. Erector spinae muscle activity was recorded using high-density EMG. Trunk kinematics during perturbation trials were collected using a 3-D motion analysis system. A two-way repeated measure ANOVA was conducted to assess: (1) the adaptation effect across trials; (2) the fatigue effect; and (3) the interaction effect (fatigue × adaptation) for the baseline activity, the reflex latency, the reflex peak and trunk kinematic variables (flexion angle, velocity and time to peak velocity). Muscle activity spatial distribution before and following the fatigue task was also compared using t-tests for dependent samples. Results: An attenuation of muscle reflex peak was observed across perturbation trials before the fatigue task, but not after. The spatial distribution of muscle activity was significantly higher before the fatigue task compared to post-fatigue trials. Baseline activity showed a trend to higher values after muscle fatigue, as well as reduction through perturbation trials. Main effects of fatigue and adaptation were found for time to peak velocity. No adaptation nor fatigue effect were identified for reflex latency, flexion angle or trunk velocity. Conclusion: The results show that muscle fatigue leads to reduced spatial distribution of back muscle activity and suggest a limited ability to use across-trial redundancy to adapt EMG reflex peak and optimize spinal stabilization using retroactive control. PMID:27895569

Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots

PubMed Central

Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated movements, (2) distributed (at each leg) recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and (3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps, leg damage adaptations, as well as climbing over high obstacles. Furthermore, we demonstrate that the newly developed recurrent network based approach to online forward models outperforms the adaptive neuron forward models, which have hitherto been the state of the art, to model a subset of similar walking behaviors in walking robots. PMID:26441629

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

NASA Technical Reports Server (NTRS)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Cooperative Adaptive Output Regulation for Second-Order Nonlinear Multiagent Systems With Jointly Connected Switching Networks.

PubMed

Liu, Wei; Huang, Jie

2018-03-01

This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multiagent systems with jointly connected switching networks. The main contributions consist of the following three aspects. First, we generalize the result of the adaptive distributed observer from undirected jointly connected switching networks to directed jointly connected switching networks. Second, by performing a new coordinate and input transformation, we convert our problem into the cooperative global robust stabilization problem of a more complex augmented system via the distributed internal model principle. Third, we solve the stabilization problem by a distributed state feedback control law. Our result is illustrated by the leader-following consensus problem for a group of Van der Pol oscillators.

Autonomous watersheds: Reducing flooding and stream erosion through real-time control

NASA Astrophysics Data System (ADS)

Kerkez, B.; Wong, B. P.

2017-12-01

We introduce an analytical toolchain, based on dynamical system theory and feedback control, to determine how many control points (valves, gates, pumps, etc.) are needed to transform urban watersheds from static to adaptive. Advances and distributed sensing and control stand to fundamentally change how we manage urban watersheds. In lieu of new and costly infrastructure, the real-time control of stormwater systems will reduce flooding, mitigate stream erosion, and improve the treatment of polluted runoff. We discuss the how open source technologies, in the form of wireless sensor nodes and remotely-controllable valves (open-storm.org), have been deployed to build "smart" stormwater systems in the Midwestern US. Unlike "static" infrastructure, which cannot readily adapt to changing inputs and land uses, these distributed control assets allow entire watersheds to be reconfigured on a storm-by-storm basis. Our results show how the control of even just a few valves within urban catchments (1-10km^2) allows for the real-time "shaping" of hydrographs, which reduces downstream erosion and flooding. We also introduce an equivalence framework that can be used by decision-makers to objectively compare investments into "smart" system to more traditional solutions, such as gray and green stormwater infrastructure.

Adaptation to changes in higher-order stimulus statistics in the salamander retina.

PubMed

Tkačik, Gašper; Ghosh, Anandamohan; Schneidman, Elad; Segev, Ronen

2014-01-01

Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.

Flexible Multi agent Algorithm for Distributed Decision Making

DTIC Science & Technology

2015-01-01

How, J. P. Consensus - Based Auction Approaches for Decentralized task Assignment. Proceedings of the AIAA Guidance, Navigation, and Control...G. ; Kim, Y. Market- based Decentralized Task Assignment for Cooperative UA V Mission Including Rendezvous. Proceedings of the AIAA Guidance...scalable and adaptable to a variety of specific mission tasks . Additionally, the algorithm could easily be adapted for use on land or sea- based systems

Development of a process control computer device for the adaptation of flexible wind tunnel walls

NASA Technical Reports Server (NTRS)

Barg, J.

1982-01-01

In wind tunnel tests, the problems arise of determining the wall pressure distribution, calculating the wall contour, and controlling adjustment of the walls. This report shows how these problems have been solved for the high speed wind tunnel of the Technical University of Berlin.

Controlling vector-borne disease and adapting to climate change with novel research on disease forecasting to target new vector control materials and technologies

USDA-ARS?s Scientific Manuscript database

Population growth, frontier agricultural expansion, and urbanization transform the landscape and the surrounding ecosystem, affecting climate and interactions between animals and humans, and significantly influencing the transmission dynamics and geographic distribution of malaria, dengue and other ...

Adaptive Development

NASA Technical Reports Server (NTRS)

2005-01-01

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

Consensus-based distributed cooperative learning from closed-loop neural control systems.

PubMed

Chen, Weisheng; Hua, Shaoyong; Zhang, Huaguang

2015-02-01

In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural networks (NNs) during the control process. First, we propose a novel control scheme called distributed cooperative learning (DCL) control scheme, by establishing the communication topology among adaptive laws of NN weights to share their learned knowledge online. It is further proved that if the communication topology is undirected and connected, all estimated weights of NNs can converge to small neighborhoods around their optimal values over a domain consisting of the union of all state orbits. Second, as a corollary it is shown that the conclusion on the deterministic learning still holds in the decentralized adaptive neural control scheme where, however, the estimated weights of NNs just converge to small neighborhoods of the optimal values along their own state orbits. Thus, the learned controllers obtained by DCL scheme have the better generalization capability than ones obtained by decentralized learning method. A simulation example is provided to verify the effectiveness and advantages of the control schemes proposed in this paper.

Experimental study of an adaptive CFRC reflector for high order wave-front error correction

NASA Astrophysics Data System (ADS)

Lan, Lan; Fang, Houfei; Wu, Ke; Jiang, Shuidong; Zhou, Yang

2018-03-01

The recent radio frequency communication system developments are generating the need for creating space antennas with lightweight and high precision. The carbon fiber reinforced composite (CFRC) materials have been used to manufacture the high precision reflector. The wave-front errors caused by fabrication and on-orbit distortion are inevitable. The adaptive CFRC reflector has received much attention to do the wave-front error correction. Due to uneven stress distribution that is introduced by actuation force and fabrication, the high order wave-front errors such as print-through error is found on the reflector surface. However, the adaptive CFRC reflector with PZT actuators basically has no control authority over the high order wave-front errors. A new design architecture assembled secondary ribs at the weak triangular surfaces is presented in this paper. The virtual experimental study of the new adaptive CFRC reflector has conducted. The controllability of the original adaptive CFRC reflector and the new adaptive CFRC reflector with secondary ribs are investigated. The virtual experimental investigation shows that the new adaptive CFRC reflector is feasible and efficient to diminish the high order wave-front error.

Adaptive elimination of synchronization in coupled oscillator

NASA Astrophysics Data System (ADS)

Zhou, Shijie; Ji, Peng; Zhou, Qing; Feng, Jianfeng; Kurths, Jürgen; Lin, Wei

2017-08-01

We present here an adaptive control scheme with a feedback delay to achieve elimination of synchronization in a large population of coupled and synchronized oscillators. We validate the feasibility of this scheme not only in the coupled Kuramoto’s oscillators with a unimodal or bimodal distribution of natural frequency, but also in two representative models of neuronal networks, namely, the FitzHugh-Nagumo spiking oscillators and the Hindmarsh-Rose bursting oscillators. More significantly, we analytically illustrate the feasibility of the proposed scheme with a feedback delay and reveal how the exact topological form of the bimodal natural frequency distribution influences the scheme performance. We anticipate that our developed scheme will deepen the understanding and refinement of those controllers, e.g. techniques of deep brain stimulation, which have been implemented in remedying some synchronization-induced mental disorders including Parkinson disease and epilepsy.

Nonlinear adaptive control of grid-connected three-phase inverters for renewable energy applications

NASA Astrophysics Data System (ADS)

Mahdian-Dehkordi, N.; Namvar, M.; Karimi, H.; Piya, P.; Karimi-Ghartemani, M.

2017-01-01

Distributed generation (DG) units are often interfaced to the main grid using power electronic converters including voltage-source converters (VSCs). A VSC offers dc/ac power conversion, high controllability, and fast dynamic response. Because of nonlinearities, uncertainties, and system parameters' changes involved in the nature of a grid-connected renewable DG system, conventional linear control methods cannot completely and efficiently address all control objectives. In this paper, a nonlinear adaptive control scheme based on adaptive backstepping strategy is presented to control the operation of a grid-connected renewable DG unit. As compared to the popular vector control technique, the proposed controller offers smoother transient responses, and lower level of current distortions. The Lyapunov approach is used to establish global asymptotic stability of the proposed control system. Linearisation technique is employed to develop guidelines for parameters tuning of the controller. Extensive time-domain digital simulations are performed and presented to verify the performance of the proposed controller when employed in a VSC to control the operation of a two-stage DG unit and also that of a single-stage solar photovoltaic system. Desirable and superior performance of the proposed controller is observed.

PI and fuzzy logic controllers for shunt Active Power Filter--a report.

PubMed

P, Karuppanan; Mahapatra, Kamala Kanta

2012-01-01

This paper presents a shunt Active Power Filter (APF) for power quality improvements in terms of harmonics and reactive power compensation in the distribution network. The compensation process is based only on source current extraction that reduces the number of sensors as well as its complexity. A Proportional Integral (PI) or Fuzzy Logic Controller (FLC) is used to extract the required reference current from the distorted line-current, and this controls the DC-side capacitor voltage of the inverter. The shunt APF is implemented with PWM-current controlled Voltage Source Inverter (VSI) and the switching patterns are generated through a novel Adaptive-Fuzzy Hysteresis Current Controller (A-F-HCC). The proposed adaptive-fuzzy-HCC is compared with fixed-HCC and adaptive-HCC techniques and the superior features of this novel approach are established. The FLC based shunt APF system is validated through extensive simulation for diode-rectifier/R-L loads. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Thin, nearly wireless adaptive optical device

NASA Technical Reports Server (NTRS)

Knowles, Gareth (Inventor); Hughes, Eli (Inventor)

2008-01-01

A thin, nearly wireless adaptive optical device capable of dynamically modulating the shape of a mirror in real time to compensate for atmospheric distortions and/or variations along an optical material is provided. The device includes an optical layer, a substrate, at least one electronic circuit layer with nearly wireless architecture, an array of actuators, power electronic switches, a reactive force element, and a digital controller. Actuators are aligned so that each axis of expansion and contraction intersects both substrate and reactive force element. Electronics layer with nearly wireless architecture, power electronic switches, and digital controller are provided within a thin-film substrate. The size and weight of the adaptive optical device is solely dominated by the size of the actuator elements rather than by the power distribution system.

Thin, nearly wireless adaptive optical device

NASA Technical Reports Server (NTRS)

Knowles, Gareth (Inventor); Hughes, Eli (Inventor)

2007-01-01

A thin, nearly wireless adaptive optical device capable of dynamically modulating the shape of a mirror in real time to compensate for atmospheric distortions and/or variations along an optical material is provided. The device includes an optical layer, a substrate, at least one electronic circuit layer with nearly wireless architecture, an array of actuators, power electronic switches, a reactive force element, and a digital controller. Actuators are aligned so that each axis of expansion and contraction intersects both substrate and reactive force element. Electronics layer with nearly wireless architecture, power electronic switches, and digital controller are provided within a thin-film substrate. The size and weight of the adaptive optical device is solely dominated by the size of the actuator elements rather than by the power distribution system.

Thin nearly wireless adaptive optical device

NASA Technical Reports Server (NTRS)

Knowles, Gareth J. (Inventor); Hughes, Eli (Inventor)

2009-01-01

A thin nearly wireless adaptive optical device capable of dynamically modulating the shape of a mirror in real time to compensate for atmospheric distortions and/or variations along an optical material is provided. The device includes an optical layer, a substrate, at least one electronic circuit layer with nearly wireless architecture, an array of actuators, power electronic switches, a reactive force element, and a digital controller. Actuators are aligned so that each axis of expansion and contraction intersects both substrate and reactive force element. Electronics layer with nearly wireless architecture, power electronic switches, and digital controller are provided within a thin-film substrate. The size and weight of the adaptive optical device is solely dominated by the size of the actuator elements rather than by the power distribution system.

Bayesian adaptive bandit-based designs using the Gittins index for multi-armed trials with normally distributed endpoints.

PubMed

Smith, Adam L; Villar, Sofía S

2018-01-01

Adaptive designs for multi-armed clinical trials have become increasingly popular recently because of their potential to shorten development times and to increase patient response. However, developing response-adaptive designs that offer patient-benefit while ensuring the resulting trial provides a statistically rigorous and unbiased comparison of the different treatments included is highly challenging. In this paper, the theory of Multi-Armed Bandit Problems is used to define near optimal adaptive designs in the context of a clinical trial with a normally distributed endpoint with known variance. We report the operating characteristics (type I error, power, bias) and patient-benefit of these approaches and alternative designs using simulation studies based on an ongoing trial. These results are then compared to those recently published in the context of Bernoulli endpoints. Many limitations and advantages are similar in both cases but there are also important differences, specially with respect to type I error control. This paper proposes a simulation-based testing procedure to correct for the observed type I error inflation that bandit-based and adaptive rules can induce.

Adaptive tracking control of leader-following linear multi-agent systems with external disturbances

NASA Astrophysics Data System (ADS)

Lin, Hanquan; Wei, Qinglai; Liu, Derong; Ma, Hongwen

2016-10-01

In this paper, the consensus problem for leader-following linear multi-agent systems with external disturbances is investigated. Brownian motions are used to describe exogenous disturbances. A distributed tracking controller based on Riccati inequalities with an adaptive law for adjusting coupling weights between neighbouring agents is designed for leader-following multi-agent systems under fixed and switching topologies. In traditional distributed static controllers, the coupling weights depend on the communication graph. However, coupling weights associated with the feedback gain matrix in our method are updated by state errors between neighbouring agents. We further present the stability analysis of leader-following multi-agent systems with stochastic disturbances under switching topology. Most traditional literature requires the graph to be connected all the time, while the communication graph is only assumed to be jointly connected in this paper. The design technique is based on Riccati inequalities and algebraic graph theory. Finally, simulations are given to show the validity of our method.

Decentralized Adaptive Control For Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

Precise knowledge of dynamics not required. Proposed scheme for control of multijointed robotic manipulator calls for independent control subsystem for each joint, consisting of proportional/integral/derivative feedback controller and position/velocity/acceleration feedforward controller, both with adjustable gains. Independent joint controller compensates for unpredictable effects, gravitation, and dynamic coupling between motions of joints, while forcing joints to track reference trajectories. Scheme amenable to parallel processing in distributed computing system wherein each joint controlled by relatively simple algorithm on dedicated microprocessor.

Transformation of two and three-dimensional regions by elliptic systems

NASA Technical Reports Server (NTRS)

Mastin, C. Wayne

1991-01-01

A reliable linear system is presented for grid generation in 2-D and 3-D. The method is robust in the sense that convergence is guaranteed but is not as reliable as other nonlinear elliptic methods in generating nonfolding grids. The construction of nonfolding grids depends on having reasonable approximations of cell aspect ratios and an appropriate distribution of grid points on the boundary of the region. Some guidelines are included on approximating the aspect ratios, but little help is offered on setting up the boundary grid other than to say that in 2-D the boundary correspondence should be close to that generated by a conformal mapping. It is assumed that the functions which control the grid distribution depend only on the computational variables and not on the physical variables. Whether this is actually the case depends on how the grid is constructed. In a dynamic adaptive procedure where the grid is constructed in the process of solving a fluid flow problem, the grid is usually updated at fixed iteration counts using the current value of the control function. Since the control function is not being updated during the iteration of the grid equations, the grid construction is a linear procedure. However, in the case of a static adaptive procedure where a trial solution is computed and used to construct an adaptive grid, the control functions may be recomputed at every step of the grid iteration.

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

PubMed Central

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-12-19

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

Method and algorithm of automatic estimation of road surface type for variable damping control

NASA Astrophysics Data System (ADS)

Dąbrowski, K.; Ślaski, G.

2016-09-01

In this paper authors presented an idea of road surface estimation (recognition) on a base of suspension dynamic response signals statistical analysis. For preliminary analysis cumulated distribution function (CDF) was used, and some conclusion that various roads have responses values in a different ranges of limits for the same percentage of samples or for the same limits different percentages of samples are located within the range between limit values. That was the base for developed and presented algorithm which was tested using suspension response signals recorded during road test riding over various surfaces. Proposed algorithm can be essential part of adaptive damping control algorithm for a vehicle suspension or adaptive control strategy for suspension damping control.

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

DTIC Science & Technology

2015-05-22

sensor networks for managing power levels of wireless networks ; air and ground transportation systems for air traffic control and payload transport and... network systems, large-scale systems, adaptive control, discontinuous systems 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF...cover a broad spectrum of ap- plications including cooperative control of unmanned air vehicles, autonomous underwater vehicles, distributed sensor

Neuromorphic learning of continuous-valued mappings from noise-corrupted data. Application to real-time adaptive control

NASA Technical Reports Server (NTRS)

Troudet, Terry; Merrill, Walter C.

1990-01-01

The ability of feed-forward neural network architectures to learn continuous valued mappings in the presence of noise was demonstrated in relation to parameter identification and real-time adaptive control applications. An error function was introduced to help optimize parameter values such as number of training iterations, observation time, sampling rate, and scaling of the control signal. The learning performance depended essentially on the degree of embodiment of the control law in the training data set and on the degree of uniformity of the probability distribution function of the data that are presented to the net during sequence. When a control law was corrupted by noise, the fluctuations of the training data biased the probability distribution function of the training data sequence. Only if the noise contamination is minimized and the degree of embodiment of the control law is maximized, can a neural net develop a good representation of the mapping and be used as a neurocontroller. A multilayer net was trained with back-error-propagation to control a cart-pole system for linear and nonlinear control laws in the presence of data processing noise and measurement noise. The neurocontroller exhibited noise-filtering properties and was found to operate more smoothly than the teacher in the presence of measurement noise.

Design and realization of adaptive optical principle system without wavefront sensing

NASA Astrophysics Data System (ADS)

Wang, Xiaobin; Niu, Chaojun; Guo, Yaxing; Han, Xiang'e.

2018-02-01

In this paper, we focus on the performance improvement of the free space optical communication system and carry out the research on wavefront-sensorless adaptive optics. We use a phase only liquid crystal spatial light modulator (SLM) as the wavefront corrector. The optical intensity distribution of the distorted wavefront is detected by a CCD. We develop a wavefront controller based on ARM and a software based on the Linux operating system. The wavefront controller can control the CCD camera and the wavefront corrector. There being two SLMs in the experimental system, one simulates atmospheric turbulence and the other is used to compensate the wavefront distortion. The experimental results show that the performance quality metric (the total gray value of 25 pixels) increases from 3037 to 4863 after 200 iterations. Besides, it is demonstrated that our wavefront-sensorless adaptive optics system based on SPGD algorithm has a good performance in compensating wavefront distortion.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Adaptive, Distributed Control of Constrained Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Dynamic Reconfiguration of a RGBD Sensor Based on QoS and QoC Requirements in Distributed Systems.

PubMed

Munera, Eduardo; Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Noguera, Juan Fco Blanes

2015-07-24

The inclusion of embedded sensors into a networked system provides useful information for many applications. A Distributed Control System (DCS) is one of the clearest examples where processing and communications are constrained by the client's requirements and the capacity of the system. An embedded sensor with advanced processing and communications capabilities supplies high level information, abstracting from the data acquisition process and objects recognition mechanisms. The implementation of an embedded sensor/actuator as a Smart Resource permits clients to access sensor information through distributed network services. Smart resources can offer sensor services as well as computing, communications and peripheral access by implementing a self-aware based adaptation mechanism which adapts the execution profile to the context. On the other hand, information integrity must be ensured when computing processes are dynamically adapted. Therefore, the processing must be adapted to perform tasks in a certain lapse of time but always ensuring a minimum process quality. In the same way, communications must try to reduce the data traffic without excluding relevant information. The main objective of the paper is to present a dynamic configuration mechanism to adapt the sensor processing and communication to the client's requirements in the DCS. This paper describes an implementation of a smart resource based on a Red, Green, Blue, and Depth (RGBD) sensor in order to test the dynamic configuration mechanism presented.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

PubMed

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

2017-04-01

Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson's disease, and helps inform how adaptive deep brain stimulation might best be delivered. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease

PubMed Central

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M.; Tan, Huiling

2017-01-01

Abstract Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson’s disease, elevations in beta activity (13–35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson’s disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson’s disease, and helps inform how adaptive deep brain stimulation might best be delivered. PMID:28334851

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

NASA Astrophysics Data System (ADS)

Cui, Bing; Zhao, Chunhui; Ma, Tiedong; Feng, Chi

2017-02-01

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.

Using Response-Time Constraints in Item Selection To Control for Differential Speededness in Computerized Adaptive Testing. LSAC Research Report Series.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L.

This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…

State estimation for distributed systems with sensing delay

NASA Astrophysics Data System (ADS)

Alexander, Harold L.

1991-08-01

Control of complex systems such as remote robotic vehicles requires combining data from many sensors where the data may often be delayed by sensory processing requirements. The number and variety of sensors make it desirable to distribute the computational burden of sensing and estimation among multiple processors. Classic Kalman filters do not lend themselves to distributed implementations or delayed measurement data. The alternative Kalman filter designs presented in this paper are adapted for delays in sensor data generation and for distribution of computation for sensing and estimation over a set of networked processors.

The Basal Ganglia and Adaptive Motor Control

NASA Astrophysics Data System (ADS)

Graybiel, Ann M.; Aosaki, Toshihiko; Flaherty, Alice W.; Kimura, Minoru

1994-09-01

The basal ganglia are neural structures within the motor and cognitive control circuits in the mammalian forebrain and are interconnected with the neocortex by multiple loops. Dysfunction in these parallel loops caused by damage to the striatum results in major defects in voluntary movement, exemplified in Parkinson's disease and Huntington's disease. These parallel loops have a distributed modular architecture resembling local expert architectures of computational learning models. During sensorimotor learning, such distributed networks may be coordinated by widely spaced striatal interneurons that acquire response properties on the basis of experienced reward.

Incipient fault detection and power system protection for spaceborne systems

NASA Technical Reports Server (NTRS)

Russell, B. Don; Hackler, Irene M.

1987-01-01

A program was initiated to study the feasibility of using advanced terrestrial power system protection techniques for spacecraft power systems. It was designed to enhance and automate spacecraft power distribution systems in the areas of safety, reliability and maintenance. The proposed power management/distribution system is described as well as security assessment and control, incipient and low current fault detection, and the proposed spaceborne protection system. It is noted that the intelligent remote power controller permits the implementation of digital relaying algorithms with both adaptive and programmable characteristics.

Observer-based distributed adaptive iterative learning control for linear multi-agent systems

NASA Astrophysics Data System (ADS)

Li, Jinsha; Liu, Sanyang; Li, Junmin

2017-10-01

This paper investigates the consensus problem for linear multi-agent systems from the viewpoint of two-dimensional systems when the state information of each agent is not available. Observer-based fully distributed adaptive iterative learning protocol is designed in this paper. A local observer is designed for each agent and it is shown that without using any global information about the communication graph, all agents achieve consensus perfectly for all undirected connected communication graph when the number of iterations tends to infinity. The Lyapunov-like energy function is employed to facilitate the learning protocol design and property analysis. Finally, simulation example is given to illustrate the theoretical analysis.

Connectivity-Preserving Approach for Distributed Adaptive Synchronized Tracking of Networked Uncertain Nonholonomic Mobile Robots.

PubMed

Yoo, Sung Jin; Park, Bong Seok

2017-09-06

This paper addresses a distributed connectivity-preserving synchronized tracking problem of multiple uncertain nonholonomic mobile robots with limited communication ranges. The information of the time-varying leader robot is assumed to be accessible to only a small fraction of follower robots. The main contribution of this paper is to introduce a new distributed nonlinear error surface for dealing with both the synchronized tracking and the preservation of the initial connectivity patterns among nonholonomic robots. Based on this nonlinear error surface, the recursive design methodology is presented to construct the approximation-based local adaptive tracking scheme at the robot dynamic level. Furthermore, a technical lemma is established to analyze the stability and the connectivity preservation of the total closed-loop control system in the Lyapunov sense. An example is provided to illustrate the effectiveness of the proposed methodology.

Adaptive Fault-Resistant Systems

DTIC Science & Technology

1994-10-01

An Architectural Overview of the Alpha Real-Time Distributed Kernel . In Proceeding., of the USEN[X Workshop on Microkernels and Other Kernel ...system and the controller are monolithic . We have noted earlier some of the problems of distributed systems-for exam- ple, the need to bound the...are monolithic . In practice, designers employ a layered structuring for their systems in order to manage complexity, and we expect that practical

Programming model for distributed intelligent systems

NASA Technical Reports Server (NTRS)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Counting Dependence Predictors

DTIC Science & Technology

2008-05-02

sophisticated dependence predictors, such as Store Sets, have been tightly coupled to the fetch and ex- ecution streams, requiring global knowledge of...applicable to any architecture with distributed fetch and distributed memory banks, in which the comprehensive event completion knowledge needed by previous...adapted for Core Fusion [5] by giv- ing its steering management unit (SMU) the responsibilities of the controller core. While Ipek et al. describe how a

Topology optimization of pressure adaptive honeycomb for a morphing flap

NASA Astrophysics Data System (ADS)

Vos, Roelof; Scheepstra, Jan; Barrett, Ron

2011-03-01

The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynamic shape changes from one flight state to the next. More modern pneumatic actuators, including FAA certified autopilot servoactuators are frequently used by aircraft around the world. Pneumatic artificial muscles (PAM) show good promise as aircraft actuators, but follow the traditional model of load concentration and distribution commonly found in aircraft. A new system is proposed which leaves distributed loads distributed and manipulates structures through a distributed actuator. By using Pressure Adaptive Honeycomb (PAH), it is shown that large structural deformations in excess of 50% strains can be achieved while maintaining full structural integrity and enabling secondary flight control mechanisms like flaps. The successful implementation of pressure-adaptive honeycomb in the trailing edge of a wing section sparked the motivation for subsequent research into the optimal topology of the pressure adaptive honeycomb within the trailing edge of a morphing flap. As an input for the optimization two known shapes are required: a desired shape in cruise configuration and a desired shape in landing configuration. In addition, the boundary conditions and load cases (including aerodynamic loads and internal pressure loads) should be specified for each condition. Finally, a set of six design variables is specified relating to the honeycomb and upper skin topology of the morphing flap. A finite-element model of the pressure-adaptive honeycomb structure is developed specifically tailored to generate fast but reliable results for a given combination of external loading, input variables, and boundary conditions. Based on two bench tests it is shown that this model correlates well to experimental results. The optimization process finds the skin and honeycomb topology that minimizes the error between the acquired shape and the desired shape in each configuration.

A new multiscale air quality transport model (Fluidity, 4.1.9) using fully unstructured anisotropic adaptive mesh technology

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-06-01

A new anisotropic hr-adaptive mesh technique has been applied to modelling of multiscale transport phenomena, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been setup for two-dimensional (2-D) transport phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes.

Multi Car Elevator Control by using Learning Automaton

NASA Astrophysics Data System (ADS)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

A map of local adaptation in Arabidopsis thaliana.

PubMed

Fournier-Level, A; Korte, A; Cooper, M D; Nordborg, M; Schmitt, J; Wilczek, A M

2011-10-07

Local adaptation is critical for species persistence in the face of rapid environmental change, but its genetic basis is not well understood. Growing the model plant Arabidopsis thaliana in field experiments in four sites across the species' native range, we identified candidate loci for local adaptation from a genome-wide association study of lifetime fitness in geographically diverse accessions. Fitness-associated loci exhibited both geographic and climatic signatures of local adaptation. Relative to genomic controls, high-fitness alleles were generally distributed closer to the site where they increased fitness, occupying specific and distinct climate spaces. Independent loci with different molecular functions contributed most strongly to fitness variation in each site. Independent local adaptation by distinct genetic mechanisms may facilitate a flexible evolutionary response to changing environment across a species range.

Dosimetric and radiobiological consequences of computed tomography-guided adaptive strategies for intensity modulated radiation therapy of the prostate.

PubMed

Battista, Jerry J; Johnson, Carol; Turnbull, David; Kempe, Jeff; Bzdusek, Karl; Van Dyk, Jacob; Bauman, Glenn

2013-12-01

To examine a range of scenarios for image-guided adaptive radiation therapy of prostate cancer, including different schedules for megavoltage CT imaging, patient repositioning, and dose replanning. We simulated multifraction dose distributions with deformable registration using 35 sets of megavoltage CT scans of 13 patients. We computed cumulative dose-volume histograms, from which tumor control probabilities and normal tissue complication probabilities (NTCPs) for rectum were calculated. Five-field intensity modulated radiation therapy (IMRT) with 18-MV x-rays was planned to achieve an isocentric dose of 76 Gy to the clinical target volume (CTV). The differences between D95, tumor control probability, V70Gy, and NTCP for rectum, for accumulated versus planned dose distributions, were compared for different target volume sizes, margins, and adaptive strategies. The CTV D95 for IMRT treatment plans, averaged over 13 patients, was 75.2 Gy. Using the largest CTV margins (10/7 mm), the D95 values accumulated over 35 fractions were within 2% of the planned value, regardless of the adaptive strategy used. For tighter margins (5 mm), the average D95 values dropped to approximately 73.0 Gy even with frequent repositioning, and daily replanning was necessary to correct this deficit. When personalized margins were applied to an adaptive CTV derived from the first 6 treatment fractions using the STAPLE (Simultaneous Truth and Performance Level Estimation) algorithm, target coverage could be maintained using a single replan 1 week into therapy. For all approaches, normal tissue parameters (rectum V(70Gy) and NTCP) remained within acceptable limits. The frequency of adaptive interventions depends on the size of the CTV combined with target margins used during IMRT optimization. The application of adaptive target margins (<5 mm) to an adaptive CTV determined 1 week into therapy minimizes the need for subsequent dose replanning. Copyright © 2013 Elsevier Inc. All rights reserved.

A new adaptive self-tuning Fourier coefficients algorithm for periodic torque ripple minimization in permanent magnet synchronous motors (PMSM).

PubMed

Gómez-Espinosa, Alfonso; Hernández-Guzmán, Víctor M; Bandala-Sánchez, Manuel; Jiménez-Hernández, Hugo; Rivas-Araiza, Edgar A; Rodríguez-Reséndiz, Juvenal; Herrera-Ruíz, Gilberto

2013-03-19

A New Adaptive Self-Tuning Fourier Coefficients Algorithm for Periodic Torque Ripple Minimization in Permanent Magnet Synchronous Motors (PMSM) Torque ripple occurs in Permanent Magnet Synchronous Motors (PMSMs) due to the non-sinusoidal flux density distribution around the air-gap and variable magnetic reluctance of the air-gap due to the stator slots distribution. These torque ripples change periodically with rotor position and are apparent as speed variations, which degrade the PMSM drive performance, particularly at low speeds, because of low inertial filtering. In this paper, a new self-tuning algorithm is developed for determining the Fourier Series Controller coefficients with the aim of reducing the torque ripple in a PMSM, thus allowing for a smoother operation. This algorithm adjusts the controller parameters based on the component's harmonic distortion in time domain of the compensation signal. Experimental evaluation is performed on a DSP-controlled PMSM evaluation platform. Test results obtained validate the effectiveness of the proposed self-tuning algorithm, with the Fourier series expansion scheme, in reducing the torque ripple.

Neural Mechanisms Behind Identification of Leptokurtic Noise and Adaptive Behavioral Response

PubMed Central

d'Acremont, Mathieu; Bossaerts, Peter

2016-01-01

Large-scale human interaction through, for example, financial markets causes ceaseless random changes in outcome variability, producing frequent and salient outliers that render the outcome distribution more peaked than the Gaussian distribution, and with longer tails. Here, we study how humans cope with this evolutionary novel leptokurtic noise, focusing on the neurobiological mechanisms that allow the brain, 1) to recognize the outliers as noise and 2) to regulate the control necessary for adaptive response. We used functional magnetic resonance imaging, while participants tracked a target whose movements were affected by leptokurtic noise. After initial overreaction and insufficient subsequent correction, participants improved performance significantly. Yet, persistently long reaction times pointed to continued need for vigilance and control. We ran a contrasting treatment where outliers reflected permanent moves of the target, as in traditional mean-shift paradigms. Importantly, outliers were equally frequent and salient. There, control was superior and reaction time was faster. We present a novel reinforcement learning model that fits observed choices better than the Bayes-optimal model. Only anterior insula discriminated between the 2 types of outliers. In both treatments, outliers initially activated an extensive bottom-up attention and belief network, followed by sustained engagement of the fronto-parietal control network. PMID:26850528

Effects of payoff functions and preference distributions in an adaptive population

NASA Astrophysics Data System (ADS)

Yang, H. M.; Ting, Y. S.; Wong, K. Y. Michael

2008-03-01

Adaptive populations such as those in financial markets and distributed control can be modeled by the Minority Game. We consider how their dynamics depends on the agents’ initial preferences of strategies, when the agents use linear or quadratic payoff functions to evaluate their strategies. We find that the fluctuations of the population making certain decisions (the volatility) depends on the diversity of the distribution of the initial preferences of strategies. When the diversity decreases, more agents tend to adapt their strategies together. In systems with linear payoffs, this results in dynamical transitions from vanishing volatility to a nonvanishing one. For low signal dimensions, the dynamical transitions for the different signals do not take place at the same critical diversity. Rather, a cascade of dynamical transitions takes place when the diversity is reduced. In contrast, no phase transitions are found in systems with the quadratic payoffs. Instead, a basin boundary of attraction separates two groups of samples in the space of the agents’ decisions. Initial states inside this boundary converge to small volatility, while those outside diverge to a large one. Furthermore, when the preference distribution becomes more polarized, the dynamics becomes more erratic. All the above results are supported by good agreement between simulations and theory.

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

Neuromusculoskeletal models based on the muscle synergy hypothesis for the investigation of adaptive motor control in locomotion via sensory-motor coordination.

PubMed

Aoi, Shinya; Funato, Tetsuro

2016-03-01

Humans and animals walk adaptively in diverse situations by skillfully manipulating their complicated and redundant musculoskeletal systems. From an analysis of measured electromyographic (EMG) data, it appears that despite complicated spatiotemporal properties, muscle activation patterns can be explained by a low dimensional spatiotemporal structure. More specifically, they can be accounted for by the combination of a small number of basic activation patterns. The basic patterns and distribution weights indicate temporal and spatial structures, respectively, and the weights show the muscle sets that are activated synchronously. In addition, various locomotor behaviors have similar low dimensional structures and major differences appear in the basic patterns. These analysis results suggest that neural systems use muscle group combinations to solve motor control redundancy problems (muscle synergy hypothesis) and manipulate those basic patterns to create various locomotor functions. However, it remains unclear how the neural system controls such muscle groups and basic patterns through neuromechanical interactions in order to achieve adaptive locomotor behavior. This paper reviews simulation studies that explored adaptive motor control in locomotion via sensory-motor coordination using neuromusculoskeletal models based on the muscle synergy hypothesis. Herein, the neural mechanism in motor control related to the muscle synergy for adaptive locomotion and a potential muscle synergy analysis method including neuromusculoskeletal modeling for motor impairments and rehabilitation are discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Adaptive Multi-Agent Systems for Constrained Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Product Distribution Theory and Semi-Coordinate Transformations

NASA Technical Reports Server (NTRS)

Airiau, Stephane; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for doing distributed adaptive control of a multiagent system (MAS). We introduce the technique of "coordinate transformations" in PD theory gradient descent. These transformations selectively couple a few agents with each other into "meta-agents". Intuitively, this can be viewed as a generalization of forming binding contracts between those agents. Doing this sacrifices a bit of the distributed nature of the MAS, in that there must now be communication from multiple agents in determining what joint-move is finally implemented However, as we demonstrate in computer experiments, these transformations improve the performance of the MAS.

Distributed and self-adaptive vehicle speed estimation in the composite braking case for four-wheel drive hybrid electric car

NASA Astrophysics Data System (ADS)

Zhao, Z.-G.; Zhou, L.-J.; Zhang, J.-T.; Zhu, Q.; Hedrick, J.-K.

2017-05-01

Considering the controllability and observability of the braking torques of the hub motor, Integrated Starter Generator (ISG), and hydraulic brake for four-wheel drive (4WD) hybrid electric cars, a distributed and self-adaptive vehicle speed estimation algorithm for different braking situations has been proposed by fully utilising the Electronic Stability Program (ESP) sensor signals and multiple powersource signals. Firstly, the simulation platform of a 4WD hybrid electric car was established, which integrates an electronic-hydraulic composited braking system model and its control strategy, a nonlinear seven degrees-of-freedom vehicle dynamics model, and the Burckhardt tyre model. Secondly, combining the braking torque signals with the ESP signals, self-adaptive unscented Kalman sub-filter and main-filter adaptable to the observation noise were, respectively, designed. Thirdly, the fusion rules for the sub-filters and master filter were proposed herein, and the estimation results were compared with the simulated value of a real vehicle speed. Finally, based on the hardware in-the-loop platform and by picking up the regenerative motor torque signals and wheel cylinder pressure signals, the proposed speed estimation algorithm was tested under the case of moderate braking on the highly adhesive road, and the case of Antilock Braking System (ABS) action on the slippery road, as well as the case of ABS action on the icy road. Test results show that the presented vehicle speed estimation algorithm has not only a high precision but also a strong adaptability in the composite braking case.

Neural network based adaptive output feedback control: Applications and improvements

NASA Astrophysics Data System (ADS)

Kutay, Ali Turker

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

Instrument control software development process for the multi-star AO system ARGOS

NASA Astrophysics Data System (ADS)

Kulas, M.; Barl, L.; Borelli, J. L.; Gässler, W.; Rabien, S.

2012-09-01

The ARGOS project (Advanced Rayleigh guided Ground layer adaptive Optics System) will upgrade the Large Binocular Telescope (LBT) with an AO System consisting of six Rayleigh laser guide stars. This adaptive optics system integrates several control loops and many different components like lasers, calibration swing arms and slope computers that are dispersed throughout the telescope. The purpose of the instrument control software (ICS) is running this AO system and providing convenient client interfaces to the instruments and the control loops. The challenges for the ARGOS ICS are the development of a distributed and safety-critical software system with no defects in a short time, the creation of huge and complex software programs with a maintainable code base, the delivery of software components with the desired functionality and the support of geographically distributed project partners. To tackle these difficult tasks, the ARGOS software engineers reuse existing software like the novel middleware from LINC-NIRVANA, an instrument for the LBT, provide many tests at different functional levels like unit tests and regression tests, agree about code and architecture style and deliver software incrementally while closely collaborating with the project partners. Many ARGOS ICS components are already successfully in use in the laboratories for testing ARGOS control loops.

Processes affecting altitudinal distribution of invasive Ageratina adenophora in western Himalaya: The role of local adaptation and the importance of different life-cycle stages

PubMed Central

Kühn, Ingolf; Ahmad, Mustaqeem; Michalski, Stefan; Auge, Harald

2017-01-01

The spread of invasive plants along elevational gradients is considered a threat to fragile mountain ecosystems, but it can also provide the opportunity to better understand some of the basic processes driving the success of invasive species. Ageratina adenophora (Asteraceae) is an invasive plant of global importance and has a broad distribution along elevational gradients in the Western Himalayas. Our study aimed at understanding the role of evolutionary processes (e.g. local adaptation and clinal differentiation) and different life history stages in shaping the distribution pattern of the invasive plant along an elevational gradient in the Western Himalaya. We carried out extensive distributional surveys, established a reciprocal transplant experiment with common gardens at three elevational levels, and measured a suite of traits related to germination, growth, reproduction and phenology. Our results showed a lack of local adaptation, and we did not find any evidence for clinal differentiation in any measured trait except a rather weak signal for plant height. We found that seed germination was the crucial life-cycle transition in determining the lower range limit while winter mortality of plants shaped the upper range limit in our study area, thus explaining the hump shaped distribution pattern. Differences in trait values between gardens for most traits indicated a high degree of phenotypic plasticity. Possible causes such as apomixis, seed dispersal among sites, and pre-adaptation might have confounded evolutionary processes to act upon. Our results suggest that the success and spread of Ageratina adenophora are dependent on different life history stages at different elevations that are controlled by abiotic conditions. PMID:29125852

Processes affecting altitudinal distribution of invasive Ageratina adenophora in western Himalaya: The role of local adaptation and the importance of different life-cycle stages.

PubMed

Datta, Arunava; Kühn, Ingolf; Ahmad, Mustaqeem; Michalski, Stefan; Auge, Harald

2017-01-01

The spread of invasive plants along elevational gradients is considered a threat to fragile mountain ecosystems, but it can also provide the opportunity to better understand some of the basic processes driving the success of invasive species. Ageratina adenophora (Asteraceae) is an invasive plant of global importance and has a broad distribution along elevational gradients in the Western Himalayas. Our study aimed at understanding the role of evolutionary processes (e.g. local adaptation and clinal differentiation) and different life history stages in shaping the distribution pattern of the invasive plant along an elevational gradient in the Western Himalaya. We carried out extensive distributional surveys, established a reciprocal transplant experiment with common gardens at three elevational levels, and measured a suite of traits related to germination, growth, reproduction and phenology. Our results showed a lack of local adaptation, and we did not find any evidence for clinal differentiation in any measured trait except a rather weak signal for plant height. We found that seed germination was the crucial life-cycle transition in determining the lower range limit while winter mortality of plants shaped the upper range limit in our study area, thus explaining the hump shaped distribution pattern. Differences in trait values between gardens for most traits indicated a high degree of phenotypic plasticity. Possible causes such as apomixis, seed dispersal among sites, and pre-adaptation might have confounded evolutionary processes to act upon. Our results suggest that the success and spread of Ageratina adenophora are dependent on different life history stages at different elevations that are controlled by abiotic conditions.

Extended state observer based robust adaptive control on SE(3) for coupled spacecraft tracking maneuver with actuator saturation and misalignment

NASA Astrophysics Data System (ADS)

Zhang, Jianqiao; Ye, Dong; Sun, Zhaowei; Liu, Chuang

2018-02-01

This paper presents a robust adaptive controller integrated with an extended state observer (ESO) to solve coupled spacecraft tracking maneuver in the presence of model uncertainties, external disturbances, actuator uncertainties including magnitude deviation and misalignment, and even actuator saturation. More specifically, employing the exponential coordinates on the Lie group SE(3) to describe configuration tracking errors, the coupled six-degrees-of-freedom (6-DOF) dynamics are developed for spacecraft relative motion, in which a generic fully actuated thruster distribution is considered and the lumped disturbances are reconstructed by using anti-windup technique. Then, a novel ESO, developed via second order sliding mode (SOSM) technique and adding linear correction terms to improve the performance, is designed firstly to estimate the disturbances in finite time. Based on the estimated information, an adaptive fast terminal sliding mode (AFTSM) controller is developed to guarantee the almost global asymptotic stability of the resulting closed-loop system such that the trajectory can be tracked with all the aforementioned drawbacks addressed simultaneously. Finally, the effectiveness of the controller is illustrated through numerical examples.

Distributed Fault-Tolerant Control of Networked Uncertain Euler-Lagrange Systems Under Actuator Faults.

PubMed

Chen, Gang; Song, Yongduan; Lewis, Frank L

2016-05-03

This paper investigates the distributed fault-tolerant control problem of networked Euler-Lagrange systems with actuator and communication link faults. An adaptive fault-tolerant cooperative control scheme is proposed to achieve the coordinated tracking control of networked uncertain Lagrange systems on a general directed communication topology, which contains a spanning tree with the root node being the active target system. The proposed algorithm is capable of compensating for the actuator bias fault, the partial loss of effectiveness actuation fault, the communication link fault, the model uncertainty, and the external disturbance simultaneously. The control scheme does not use any fault detection and isolation mechanism to detect, separate, and identify the actuator faults online, which largely reduces the online computation and expedites the responsiveness of the controller. To validate the effectiveness of the proposed method, a test-bed of multiple robot-arm cooperative control system is developed for real-time verification. Experiments on the networked robot-arms are conduced and the results confirm the benefits and the effectiveness of the proposed distributed fault-tolerant control algorithms.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Center for Adaptive Optics | Software

Science.gov Websites

Center for Adaptive Optics A University of California Science and Technology Center home Adaptive Optics Software The Center for Adaptive Optics acts as a clearing house for distributing Software to Institutes it gives specialists in Adaptive Optics a place to distribute their software. All software is

Multiple testing with discrete data: Proportion of true null hypotheses and two adaptive FDR procedures.

PubMed

Chen, Xiongzhi; Doerge, Rebecca W; Heyse, Joseph F

2018-05-11

We consider multiple testing with false discovery rate (FDR) control when p values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, that is, an adaptive Benjamini-Hochberg (BH) procedure and an adaptive Benjamini-Hochberg-Heyse (BHH) procedure. We prove that the adaptive BH (aBH) procedure is conservative nonasymptotically. Through simulation studies, we show that these procedures are usually more powerful than their nonadaptive counterparts and that the adaptive BHH procedure is usually more powerful than the aBH procedure and a procedure based on randomized p-value. The adaptive procedures are applied to a study of HIV vaccine efficacy, where they identify more differentially polymorphic positions than the BH procedure at the same FDR level. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Wave field synthesis, adaptive wave field synthesis and ambisonics using decentralized transformed control: Potential applications to sound field reproduction and active noise control

NASA Astrophysics Data System (ADS)

Gauthier, Philippe-Aubert; Berry, Alain; Woszczyk, Wieslaw

2005-09-01

Sound field reproduction finds applications in listening to prerecorded music or in synthesizing virtual acoustics. The objective is to recreate a sound field in a listening environment. Wave field synthesis (WFS) is a known open-loop technology which assumes that the reproduction environment is anechoic. Classical WFS, therefore, does not perform well in a real reproduction space such as room. Previous work has suggested that it is physically possible to reproduce a progressive wave field in-room situation using active control approaches. In this paper, a formulation of adaptive wave field synthesis (AWFS) introduces practical possibilities for an adaptive sound field reproduction combining WFS and active control (with WFS departure penalization) with a limited number of error sensors. AWFS includes WFS and closed-loop ``Ambisonics'' as limiting cases. This leads to the modification of the multichannel filtered-reference least-mean-square (FXLMS) and the filtered-error LMS (FELMS) adaptive algorithms for AWFS. Decentralization of AWFS for sound field reproduction is introduced on the basis of sources' and sensors' radiation modes. Such decoupling may lead to decentralized control of source strength distributions and may reduce computational burden of the FXLMS and the FELMS algorithms used for AWFS. [Work funded by NSERC, NATEQ, Université de Sherbrooke and VRQ.] Ultrasound/Bioresponse to

Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass.

PubMed

Jueterbock, A; Franssen, S U; Bergmann, N; Gu, J; Coyer, J A; Reusch, T B H; Bornberg-Bauer, E; Olsen, J L

2016-11-01

Populations distributed across a broad thermal cline are instrumental in addressing adaptation to increasing temperatures under global warming. Using a space-for-time substitution design, we tested for parallel adaptation to warm temperatures along two independent thermal clines in Zostera marina, the most widely distributed seagrass in the temperate Northern Hemisphere. A North-South pair of populations was sampled along the European and North American coasts and exposed to a simulated heatwave in a common-garden mesocosm. Transcriptomic responses under control, heat stress and recovery were recorded in 99 RNAseq libraries with ~13 000 uniquely annotated, expressed genes. We corrected for phylogenetic differentiation among populations to discriminate neutral from adaptive differentiation. The two southern populations recovered faster from heat stress and showed parallel transcriptomic differentiation, as compared with northern populations. Among 2389 differentially expressed genes, 21 exceeded neutral expectations and were likely involved in parallel adaptation to warm temperatures. However, the strongest differentiation following phylogenetic correction was between the three Atlantic populations and the Mediterranean population with 128 of 4711 differentially expressed genes exceeding neutral expectations. Although adaptation to warm temperatures is expected to reduce sensitivity to heatwaves, the continued resistance of seagrass to further anthropogenic stresses may be impaired by heat-induced downregulation of genes related to photosynthesis, pathogen defence and stress tolerance. © 2016 John Wiley & Sons Ltd.

Distributed wavefront reconstruction with SABRE for real-time large scale adaptive optics control

NASA Astrophysics Data System (ADS)

Brunner, Elisabeth; de Visser, Cornelis C.; Verhaegen, Michel

2014-08-01

We present advances on Spline based ABerration REconstruction (SABRE) from (Shack-)Hartmann (SH) wavefront measurements for large-scale adaptive optics systems. SABRE locally models the wavefront with simplex B-spline basis functions on triangular partitions which are defined on the SH subaperture array. This approach allows high accuracy through the possible use of nonlinear basis functions and great adaptability to any wavefront sensor and pupil geometry. The main contribution of this paper is a distributed wavefront reconstruction method, D-SABRE, which is a 2 stage procedure based on decomposing the sensor domain into sub-domains each supporting a local SABRE model. D-SABRE greatly decreases the computational complexity of the method and removes the need for centralized reconstruction while obtaining a reconstruction accuracy for simulated E-ELT turbulences within 1% of the global method's accuracy. Further, a generalization of the methodology is proposed making direct use of SH intensity measurements which leads to an improved accuracy of the reconstruction compared to centroid algorithms using spatial gradients.

Development of adaptive observation strategy using retrospective optimal interpolation

NASA Astrophysics Data System (ADS)

Noh, N.; Kim, S.; Song, H.; Lim, G.

2011-12-01

Retrospective optimal interpolation (ROI) is a method that is used to minimize cost functions with multiple minima without using adjoint models. Song and Lim (2011) perform the experiments to reduce the computational costs for implementing ROI by transforming the control variables into eigenvectors of background error covariance. We adapt the ROI algorithm to compute sensitivity estimates of severe weather events over the Korean peninsula. The eigenvectors of the ROI algorithm is modified every time the observations are assimilated. This implies that the modified eigenvectors shows the error distribution of control variables which are updated by assimilating observations. So, We can estimate the effects of the specific observations. In order to verify the adaptive observation strategy, High-impact weather over the Korean peninsula is simulated and interpreted using WRF modeling system and sensitive regions for each high-impact weather is calculated. The effects of assimilation for each observation type is discussed.

FISHER'S GEOMETRIC MODEL WITH A MOVING OPTIMUM

PubMed Central

Matuszewski, Sebastian; Hermisson, Joachim; Kopp, Michael

2014-01-01

Fisher's geometric model has been widely used to study the effects of pleiotropy and organismic complexity on phenotypic adaptation. Here, we study a version of Fisher's model in which a population adapts to a gradually moving optimum. Key parameters are the rate of environmental change, the dimensionality of phenotype space, and the patterns of mutational and selectional correlations. We focus on the distribution of adaptive substitutions, that is, the multivariate distribution of the phenotypic effects of fixed beneficial mutations. Our main results are based on an “adaptive-walk approximation,” which is checked against individual-based simulations. We find that (1) the distribution of adaptive substitutions is strongly affected by the ecological dynamics and largely depends on a single composite parameter γ, which scales the rate of environmental change by the “adaptive potential” of the population; (2) the distribution of adaptive substitution reflects the shape of the fitness landscape if the environment changes slowly, whereas it mirrors the distribution of new mutations if the environment changes fast; (3) in contrast to classical models of adaptation assuming a constant optimum, with a moving optimum, more complex organisms evolve via larger adaptive steps. PMID:24898080

ISIS and META projects

NASA Technical Reports Server (NTRS)

Birman, Kenneth; Cooper, Robert; Marzullo, Keith

1990-01-01

The ISIS project has developed a new methodology, virtual synchony, for writing robust distributed software. High performance multicast, large scale applications, and wide area networks are the focus of interest. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project is distributed control in a soft real-time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor, and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are reported.

An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition

PubMed Central

Brainard, Michael S.; Jin, Dezhe Z.

2015-01-01

Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds. We propose that auditory signals provide positive feedback to ongoing motor commands, but this influence decays as feedback weakens from response adaptation during syllable repetitions. Computational models show that this mechanism explains repeat distributions observed in Bengalese finch song. We experimentally confirmed two predictions of this mechanism in Bengalese finches: removal of auditory feedback by deafening reduces syllable repetitions; and neural responses to auditory playback of repeated syllable sequences gradually adapt in sensory-motor nucleus HVC. Together, our results implicate a positive auditory-feedback loop with adaptation in generating repetitive vocalizations, and suggest sensory adaptation is important for feedback control of motor sequences. PMID:26448054

Adaptive Helmholtz resonators and passive vibration absorbers for cylinder interior noise control

NASA Astrophysics Data System (ADS)

Estève, Simon J.; Johnson, Marty E.

2005-12-01

This paper presents an adaptive-passive solution to control the broadband sound transmission into rocket payload fairings. The treatment is composed of passive distributed vibration absorbers (DVAs) and adaptive Helmholtz resonators (HR). Both the frequency domain and time-domain model of a simply supported cylinder excited by an external plane wave are developed. To tune vibration absorbers to tonal excitation, a tuning strategy, based on the phase information between the velocity of the absorber mass and the velocity of the host structure is used here in a new fashion to tune resonators to peaks in the broadband acoustic spectrum of a cavity. This tuning law, called the dot-product method, only uses two microphone signals local to each HR, which allows the adaptive Helmholtz resonator (AHR) to be manufactured as an autonomous device with power supply, sensor, actuator and controller integrated. Numerical simulations corresponding to a 2.8 m long 2.5 m diameter composite cylinder prototype demonstrate that, as long as the structure modes, which strongly couple to the acoustic cavity, are damped with a DVA treatment, the dot-product method tune multiple HRs to a near-optimal solution over a broad frequency range (40-160 Hz). An adaptive HR prototype with variable opening is built and characterized. Experiments conducted on the cylinder prototype with eight AHRs demonstrate the ability of resonators adapted with the dot-product method to converge to near-optimal noise attenuation in a frequency band including multiple resonances.

[Application of remote sensing and GIS in study of suitability distribution of Swertia mussotii, a Tibetan medicine in Sichuan province].

PubMed

Dong, Yong-Bo; Luo, Yao; Zhu, Cong; Peng, Wen-Fu; Xu, Xin-Liang; Fang, Qing-Mao

2017-11-01

Swertia mussotii is a kind of rare medicinal materials, the relevant researches are mainly concentrated on its medicinal efficacy and medicinal value till now, researches of adaptive distribution by applying remote sensing and GIS are relatively less. This study is to analyze the adaptive distribution of S.mussotii in Sichuan province by applying remote sensing and GIS technology, and provide scientific basis for the protection and development of wild resources, artificial cultivation and adjustment of Chinese medicine industrial distribution in Sichuan province. Based on literature review and ecological factors such as altitude, annual precipitation and annual average temperature, this study extracted ecological factors, overlay analysis in GIS, as well as combining GPS field validation data by means of remote sensing and GIS, discusses the adaptive distribution of SMF sin Sichuan province. ①The area of adaptive distribution of S. mussotii in Sichuan province is 1 543.749 km², mainly in Dege county, Ganzi county, Daofu county, Kangding county, Barkam, Jinchuan county, Xiaojin county, Danba county, Daocheng county, Xiangcheng county, Xinlong county, Aba county, Muli county and other counties and cities, accounts for about 7.25% in total area. ② Combining statistical information and field validation, this study found that S. mussotii adaptive distribution gained by remote sensing and GIS is in conformity with its actual distribution. The study shows that remote sensing and GIS technology are feasible to obtain the S. mussotii adaptive distribution, they can further be applied to studies on adaptive distributions of other rare Chinese medicinal herb. Copyright© by the Chinese Pharmaceutical Association.

Arabinogalactan Proteins Are Involved in Salt-Adaptation and Vesicle Trafficking in Tobacco by-2 Cell Cultures

PubMed Central

Olmos, Enrique; García De La Garma, Jesús; Gomez-Jimenez, Maria C.; Fernandez-Garcia, Nieves

2017-01-01

Arabinogalactan proteins (AGPs) are a highly diverse family of glycoproteins that are commonly found in most plant species. However, little is known about the physiological and molecular mechanisms of their function. AGPs are involved in different biological processes such as cell differentiation, cell expansion, tissue development and somatic embryogenesis. AGPs are also involved in abiotic stress response such as salinity modulating cell wall expansion. In this study, we describe how salt-adaptation in tobacco BY-2 cell cultures induces important changes in arabinogalactan proteins distribution and contents. Using the immuno-dot blot technique with different anti-AGP antibodies (JIM13, JIM15, and others), we observed that AGPs were highly accumulated in the culture medium of salt-adapted tobacco cells, probably due to the action of phospholipases. We located these AGP epitopes using immunogold labeling in the cytoplasm associated to the endoplasmic reticulum, the golgi apparatus, and vesicles, plasma membrane and tonoplast. Our results show that salt-adaptation induced a significant reduction of the cytoplasm, plasma membrane and tonoplast content of these epitopes. Yariv reagent was added to the control and salt-adapted tobacco cell cultures, leading to cell death induction in control cells but not in salt-adapted cells. Ultrastructural and immunogold labeling revealed that cell death induced by Yariv reagent in control cells was due to the interaction of Yariv reagent with the AGPs linked to the plasma membranes. Finally, we propose a new function of AGPs as a possible sodium carrier through the mechanism of vesicle trafficking from the apoplast to the vacuoles in salt-adapted tobacco BY-2 cells. This mechanism may contribute to sodium homeostasis during salt-adaptation to high saline concentrations. PMID:28676820

Arabinogalactan Proteins Are Involved in Salt-Adaptation and Vesicle Trafficking in Tobacco by-2 Cell Cultures.

PubMed

Olmos, Enrique; García De La Garma, Jesús; Gomez-Jimenez, Maria C; Fernandez-Garcia, Nieves

2017-01-01

Arabinogalactan proteins (AGPs) are a highly diverse family of glycoproteins that are commonly found in most plant species. However, little is known about the physiological and molecular mechanisms of their function. AGPs are involved in different biological processes such as cell differentiation, cell expansion, tissue development and somatic embryogenesis. AGPs are also involved in abiotic stress response such as salinity modulating cell wall expansion. In this study, we describe how salt-adaptation in tobacco BY-2 cell cultures induces important changes in arabinogalactan proteins distribution and contents. Using the immuno-dot blot technique with different anti-AGP antibodies (JIM13, JIM15, and others), we observed that AGPs were highly accumulated in the culture medium of salt-adapted tobacco cells, probably due to the action of phospholipases. We located these AGP epitopes using immunogold labeling in the cytoplasm associated to the endoplasmic reticulum, the golgi apparatus, and vesicles, plasma membrane and tonoplast. Our results show that salt-adaptation induced a significant reduction of the cytoplasm, plasma membrane and tonoplast content of these epitopes. Yariv reagent was added to the control and salt-adapted tobacco cell cultures, leading to cell death induction in control cells but not in salt-adapted cells. Ultrastructural and immunogold labeling revealed that cell death induced by Yariv reagent in control cells was due to the interaction of Yariv reagent with the AGPs linked to the plasma membranes. Finally, we propose a new function of AGPs as a possible sodium carrier through the mechanism of vesicle trafficking from the apoplast to the vacuoles in salt-adapted tobacco BY-2 cells. This mechanism may contribute to sodium homeostasis during salt-adaptation to high saline concentrations.

Parallel kinematic mechanisms for distributed actuation of future structures

NASA Astrophysics Data System (ADS)

Lai, G.; Plummer, A. R.; Cleaver, D. J.; Zhou, H.

2016-09-01

Future machines will require distributed actuation integrated with load-bearing structures, so that they are lighter, move faster, use less energy, and are more adaptable. Good examples are shape-changing aircraft wings which can adapt precisely to the ideal aerodynamic form for current flying conditions, and light but powerful robotic manipulators which can interact safely with human co-workers. A 'tensegrity structure' is a good candidate for this application due to its potentially excellent stiffness and strength-to-weight ratio and a multi-element structure into which actuators could be embedded. This paper presents results of an analysis of an example practical actuated tensegrity structure consisting of 3 ‘unit cells’. A numerical method is used to determine the stability of the structure with varying actuator length, showing how four actuators can be used to control movement in three degrees of freedom as well as simultaneously maintaining the structural pre-load. An experimental prototype has been built, in which 4 pneumatic artificial muscles (PAMs) are embedded in one unit cell. The PAMs are controlled antagonistically, by high speed switching of on-off valves, to achieve control of position and structure pre-load. Experimental and simulation results are presented, and future prospects for the approach are discussed.

Multi-time scale control of demand flexibility in smart distribution networks

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

Bhattarai, Bishnu; Myers, Kurt; Bak-Jensen, Birgitte

This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distributionmore » network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.« less

Multi-time scale control of demand flexibility in smart distribution networks

DOE PAGES

Bhattarai, Bishnu; Myers, Kurt; Bak-Jensen, Birgitte; ...

2017-01-01

This study presents a multi-timescale control strategy to deploy demand flexibilities of electric vehicles (EV) for providing system balancing and local congestion management by simultaneously ensuring economic benefits to participating actors. First, the EV charging problem from consumer, aggregator, and grid operator’s perspective is investigated. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating a multi-time scale control, which works from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical distributionmore » network. The simulation results demonstrates that HCA exploit EV flexibility to solve grid unbalancing and congestions with simultaneous maximization of economic benefits by ensuring EV participation to day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to 5 times the cost they were paying without control.« less

Piezoelectric actuator models for active sound and vibration control of cylinders

NASA Technical Reports Server (NTRS)

Lester, Harold C.; Lefebvre, Sylvie

1993-01-01

Analytical models for piezoelectric actuators, adapted from flat plate concepts, are developed for noise and vibration control applications associated with vibrating circular cylinders. The loadings applied to the cylinder by the piezoelectric actuators for the bending and in-plane force models are approximated by line moment and line force distributions, respectively, acting on the perimeter of the actuator patch area. Coupling between the cylinder and interior acoustic cavity is examined by studying the modal spectra, particularly for the low-order cylinder modes that couple efficiently with the cavity at low frequencies. Within the scope of this study, the in-plane force model produced a more favorable distribution of low-order modes, necessary for efficient interior noise control, than did the bending model.

Robust tracking and distributed synchronization control of a multi-motor servomechanism with H-infinity performance.

PubMed

Wang, Minlin; Ren, Xuemei; Chen, Qiang

2018-01-01

The multi-motor servomechanism (MMS) is a multi-variable, high coupling and nonlinear system, which makes the controller design challenging. In this paper, an adaptive robust H-infinity control scheme is proposed to achieve both the load tracking and multi-motor synchronization of MMS. This control scheme consists of two parts: a robust tracking controller and a distributed synchronization controller. The robust tracking controller is constructed by incorporating a neural network (NN) K-filter observer into the dynamic surface control, while the distributed synchronization controller is designed by combining the mean deviation coupling control strategy with the distributed technique. The proposed control scheme has several merits: 1) by using the mean deviation coupling synchronization control strategy, the tracking controller and the synchronization controller can be designed individually without any coupling problem; 2) the immeasurable states and unknown nonlinearities are handled by a NN K-filter observer, where the number of NN weights is largely reduced by using the minimal learning parameter technique; 3) the H-infinity performances of tracking error and synchronization error are guaranteed by introducing a robust term into the tracking controller and the synchronization controller, respectively. The stabilities of the tracking and synchronization control systems are analyzed by the Lyapunov theory. Simulation and experimental results based on a four-motor servomechanism are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

Outsourcing neural active control to passive composite mechanics: a tissue engineered cyborg ray

NASA Astrophysics Data System (ADS)

Gazzola, Mattia; Park, Sung Jin; Park, Kyung Soo; Park, Shirley; di Santo, Valentina; Deisseroth, Karl; Lauder, George V.; Mahadevan, L.; Parker, Kevin Kit

2016-11-01

Translating the blueprint that stingrays and skates provide, we create a cyborg swimming ray capable of orchestrating adaptive maneuvering and phototactic navigation. The impossibility of replicating the neural system of batoids fish is bypassed by outsourcing algorithmic functionalities to the body composite mechanics, hence casting the active control problem into a design, passive one. We present a first step in engineering multilevel "brain-body-flow" systems that couple sensory information to motor coordination and movement, leading to behavior. This work paves the way for the development of autonomous and adaptive artificial creatures able to process multiple sensory inputs and produce complex behaviors in distributed systems and may represent a path toward soft-robotic "embodied cognition".

A new solution-adaptive grid generation method for transonic airfoil flow calculations

NASA Technical Reports Server (NTRS)

Nakamura, S.; Holst, T. L.

1981-01-01

The clustering algorithm is controlled by a second-order, ordinary differential equation which uses the airfoil surface density gradient as a forcing function. The solution to this differential equation produces a surface grid distribution which is automatically clustered in regions with large gradients. The interior grid points are established from this surface distribution by using an interpolation scheme which is fast and retains the desirable properties of the original grid generated from the standard elliptic equation approach.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

PubMed Central

Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R.; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

2016-01-01

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

Streamline integration as a method for two-dimensional elliptic grid generation

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

Wiesenberger, M., E-mail: Matthias.Wiesenberger@uibk.ac.at; Held, M.; Einkemmer, L.

We propose a new numerical algorithm to construct a structured numerical elliptic grid of a doubly connected domain. Our method is applicable to domains with boundaries defined by two contour lines of a two-dimensional function. Furthermore, we can adapt any analytically given boundary aligned structured grid, which specifically includes polar and Cartesian grids. The resulting coordinate lines are orthogonal to the boundary. Grid points as well as the elements of the Jacobian matrix can be computed efficiently and up to machine precision. In the simplest case we construct conformal grids, yet with the help of weight functions and monitor metricsmore » we can control the distribution of cells across the domain. Our algorithm is parallelizable and easy to implement with elementary numerical methods. We assess the quality of grids by considering both the distribution of cell sizes and the accuracy of the solution to elliptic problems. Among the tested grids these key properties are best fulfilled by the grid constructed with the monitor metric approach. - Graphical abstract: - Highlights: • Construct structured, elliptic numerical grids with elementary numerical methods. • Align coordinate lines with or make them orthogonal to the domain boundary. • Compute grid points and metric elements up to machine precision. • Control cell distribution by adaption functions or monitor metrics.« less

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

PubMed

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

2015-11-01

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

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Adaptive Sequential Monte Carlo for Multiple Changepoint Analysis

DOE PAGES

Heard, Nicholas A.; Turcotte, Melissa J. M.

2016-05-21

Process monitoring and control requires detection of structural changes in a data stream in real time. This paper introduces an efficient sequential Monte Carlo algorithm designed for learning unknown changepoints in continuous time. The method is intuitively simple: new changepoints for the latest window of data are proposed by conditioning only on data observed since the most recent estimated changepoint, as these observations carry most of the information about the current state of the process. The proposed method shows improved performance over the current state of the art. Another advantage of the proposed algorithm is that it can be mademore » adaptive, varying the number of particles according to the apparent local complexity of the target changepoint probability distribution. This saves valuable computing time when changes in the changepoint distribution are negligible, and enables re-balancing of the importance weights of existing particles when a significant change in the target distribution is encountered. The plain and adaptive versions of the method are illustrated using the canonical continuous time changepoint problem of inferring the intensity of an inhomogeneous Poisson process, although the method is generally applicable to any changepoint problem. Performance is demonstrated using both conjugate and non-conjugate Bayesian models for the intensity. Lastly, appendices to the article are available online, illustrating the method on other models and applications.« less

Rational regional distribution of sugarcane cultivars in China

PubMed Central

Luo, Jun; Pan, Yong-Bao; Xu, Liping; Grisham, Michael Paul; Zhang, Hua; Que, Youxiong

2015-01-01

Knowing yield potential and yield stability of sugarcane cultivars is of significance in guiding sugarcane breeding and rationalising regional distribution of sugarcane cultivars. In the present study, a heritability-adjusted genotype main effect plus genotype × environment (HA-GGE) biplot program was used to analyze the cane and sucrose yields of 44 newly released sugarcane cultivars at eight pilot test sites. The cane and sucrose yields of nine cultivars were higher than those of the control cultivar ROC22. From the perspective of cane yield, cultivars FN 40 and YZ 06–407 were well adapted to a wider range of conditions and produced relatively high cane yields in several pilot sites. From the perspective of sucrose yield, cultivars LC 03–1137, FN 38, FN 41, MT 01–77 and LC 05–136 were well adapted to a wide range of conditions and produced relatively high sucrose yields. Based on these results, three high yielding and widely adapted cultivars, namely, FN 39, LC 05–136, and YZ 05–51 were recommended for production in three major Chinese sugarcane planting areas. The results will provide a theoretical basis for recommending the effective use and rational regional distribution of sugarcane cultivars in China. PMID:26499905

Decomposed fuzzy systems and their application in direct adaptive fuzzy control.

PubMed

Hsueh, Yao-Chu; Su, Shun-Feng; Chen, Ming-Chang

2014-10-01

In this paper, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator for adaptive fuzzy control systems. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems, and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables form the so-called component fuzzy systems. DFS is proposed to provide more adjustable parameters to facilitate possible adaptation in fuzzy rules, but without introducing a learning burden. It is because those component fuzzy systems are independent so that it can facilitate minimum distribution learning effects among component fuzzy systems. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this paper to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure.

A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization - abstract

EPA Science Inventory

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization

EPA Science Inventory

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

Biology Laboratory Safety Manual.

ERIC Educational Resources Information Center

Case, Christine L.

The Centers for Disease Control (CDC) recommends that schools prepare or adapt a biosafety manual, and that instructors develop a list of safety procedures applicable to their own lab and distribute it to each student. In this way, safety issues will be brought to each student's attention. This document is an example of such a manual. It contains…

FACTORS CONTROLLING ZOSTERA MARINA L. GROWTH IN THE EASTERN AND WESTERN PACIFIC OCEAN: COMPARISONS BETWEEN SOUTH KOREA AND OREGON, USA

EPA Science Inventory

Zostera marina distribution is circum-global and tolerates a wide range of environmental conditions. Consequently, it is likely that populations have adapted to local environmental conditions of light, temperature and nutrient supply. We compared Z. marina growth dynamics over a ...

Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1.

PubMed

Kronholm, Ilkka; Picó, F Xavier; Alonso-Blanco, Carlos; Goudet, Jérôme; de Meaux, Juliette

2012-07-01

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation. © 2012 The Author(s).

Execution time supports for adaptive scientific algorithms on distributed memory machines

NASA Technical Reports Server (NTRS)

Berryman, Harry; Saltz, Joel; Scroggs, Jeffrey

1990-01-01

Optimizations are considered that are required for efficient execution of code segments that consists of loops over distributed data structures. The PARTI (Parallel Automated Runtime Toolkit at ICASE) execution time primitives are designed to carry out these optimizations and can be used to implement a wide range of scientific algorithms on distributed memory machines. These primitives allow the user to control array mappings in a way that gives an appearance of shared memory. Computations can be based on a global index set. Primitives are used to carry out gather and scatter operations on distributed arrays. Communications patterns are derived at runtime, and the appropriate send and receive messages are automatically generated.

Towards a new multiscale air quality transport model using the fully unstructured anisotropic adaptive mesh technology of Fluidity (version 4.1.9)

NASA Astrophysics Data System (ADS)

Zheng, J.; Zhu, J.; Wang, Z.; Fang, F.; Pain, C. C.; Xiang, J.

2015-10-01

An integrated method of advanced anisotropic hr-adaptive mesh and discretization numerical techniques has been, for first time, applied to modelling of multiscale advection-diffusion problems, which is based on a discontinuous Galerkin/control volume discretization on unstructured meshes. Over existing air quality models typically based on static-structured grids using a locally nesting technique, the advantage of the anisotropic hr-adaptive model has the ability to adapt the mesh according to the evolving pollutant distribution and flow features. That is, the mesh resolution can be adjusted dynamically to simulate the pollutant transport process accurately and effectively. To illustrate the capability of the anisotropic adaptive unstructured mesh model, three benchmark numerical experiments have been set up for two-dimensional (2-D) advection phenomena. Comparisons have been made between the results obtained using uniform resolution meshes and anisotropic adaptive resolution meshes. Performance achieved in 3-D simulation of power plant plumes indicates that this new adaptive multiscale model has the potential to provide accurate air quality modelling solutions effectively.

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

PubMed

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

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1999-01-01

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

Network support for turn-taking in multimedia collaboration

NASA Astrophysics Data System (ADS)

Dommel, Hans-Peter; Garcia-Luna-Aceves, Jose J.

1997-01-01

The effectiveness of collaborative multimedia systems depends on the regulation of access to their shared resources, such as continuous media or instruments used concurrently by multiple parties. Existing applications use only simple protocols to mediate such resource contention. Their cooperative rules follow a strict agenda and are largely application-specific. The inherent problem of floor control lacks a systematic methodology. This paper presents a general model on floor control for correct, scalable, fine-grained and fair resource sharing that integrates user interaction with network conditions, and adaptation to various media types. The motion of turn-taking known from psycholinguistics in studies on discourse structure is adapted for this framework. Viewed as a computational analogy to speech communication, online collaboration revolves around dynamically allocated access permissions called floors. The control semantics of floors derives from concurrently control methodology. An explicit specification and verification of a novel distributed Floor Control Protocol are presented. Hosts assume sharing roles that allow for efficient dissemination of control information, agreeing on a floor holder which is granted mutually exclusive access to a resource. Performance analytic aspects of floor control protocols are also briefly discussed.

Active control of impulsive noise with symmetric α-stable distribution based on an improved step-size normalized adaptive algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yali; Zhang, Qizhi; Yin, Yixin

2015-05-01

In this paper, active control of impulsive noise with symmetric α-stable (SαS) distribution is studied. A general step-size normalized filtered-x Least Mean Square (FxLMS) algorithm is developed based on the analysis of existing algorithms, and the Gaussian distribution function is used to normalize the step size. Compared with existing algorithms, the proposed algorithm needs neither the parameter selection and thresholds estimation nor the process of cost function selection and complex gradient computation. Computer simulations have been carried out to suggest that the proposed algorithm is effective for attenuating SαS impulsive noise, and then the proposed algorithm has been implemented in an experimental ANC system. Experimental results show that the proposed scheme has good performance for SαS impulsive noise attenuation.

Holonic Rationale and Bio-inspiration on Design of Complex Emergent and Evolvable Systems

NASA Astrophysics Data System (ADS)

Leitao, Paulo

Traditional centralized and rigid control structures are becoming inflexible to face the requirements of reconfigurability, responsiveness and robustness, imposed by customer demands in the current global economy. The Holonic Manufacturing Systems (HMS) paradigm, which was pointed out as a suitable solution to face these requirements, translates the concepts inherited from social organizations and biology to the manufacturing world. It offers an alternative way of designing adaptive systems where the traditional centralized control is replaced by decentralization over distributed and autonomous entities organized in hierarchical structures formed by intermediate stable forms. In spite of its enormous potential, methods regarding the self-adaptation and self-organization of complex systems are still missing. This paper discusses how the insights from biology in connection with new fields of computer science can be useful to enhance the holonic design aiming to achieve more self-adaptive and evolvable systems. Special attention is devoted to the discussion of emergent behavior and self-organization concepts, and the way they can be combined with the holonic rationale.

Public authority control strategy for opinion evolution in social networks

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Public authority control strategy for opinion evolution in social networks.

PubMed

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

2016-08-01

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

Visual perception system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Chelian, Suhas E. (Inventor); Linn, Douglas Martin (Inventor); Wampler, II, Charles W. (Inventor); Bridgwater, Lyndon (Inventor); Wells, James W. (Inventor); Mc Kay, Neil David (Inventor)

2012-01-01

A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image.

Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles

NASA Astrophysics Data System (ADS)

Davis, L. C.

2016-06-01

Wirelessly connected vehicles that exchange information about traffic conditions can reduce delays caused by congestion. At a 2-to-1 lane reduction, the improvement in flow past a bottleneck due to traffic with a random mixture of 40% connected vehicles is found to be 52%. Control is based on connected-vehicle-reported velocities near the bottleneck. In response to indications of congestion the connected vehicles, which are also adaptive cruise control vehicles, reduce their speed in slowdown regions. Early lane changes of manually driven vehicles from the terminated lane to the continuous lane are induced by the slowing connected vehicles. Self-organized congestion at the bottleneck is thus delayed or eliminated, depending upon the incoming flow magnitude. For the large majority of vehicles, travel times past the bottleneck are substantially reduced. Control is responsible for delaying the onset of congestion as the incoming flow increases. Adaptive cruise control increases the flow out of the congested state at the bottleneck. The nature of the congested state, when it occurs, appears to be similar under a variety of conditions. Typically 80-100 vehicles are approximately equally distributed between the lanes in the 500 m region prior to the end of the terminated lane. Without the adaptive cruise control capability, connected vehicles can delay the onset of congestion but do not increase the asymptotic flow past the bottleneck. Calculations are done using the Kerner-Klenov three-phase theory, stochastic discrete-time model for manual vehicles. The dynamics of the connected vehicles is given by a conventional adaptive cruise control algorithm plus commanded deceleration. Because time in the model for manual vehicles is discrete (one-second intervals), it is assumed that the acceleration of any vehicle immediately in front of a connected vehicle is constant during the time interval, thereby preserving the computational simplicity and speed of a discrete-time model.

Power System Information Delivering System Based on Distributed Object

NASA Astrophysics Data System (ADS)

Tanaka, Tatsuji; Tsuchiya, Takehiko; Tamura, Setsuo; Seki, Tomomichi; Kubota, Kenji

In recent years, improvement in computer performance and development of computer network technology or the distributed information processing technology has a remarkable thing. Moreover, the deregulation is starting and will be spreading in the electric power industry in Japan. Consequently, power suppliers are required to supply low cost power with high quality services to customers. Corresponding to these movements the authors have been proposed SCOPE (System Configuration Of PowEr control system) architecture for distributed EMS/SCADA (Energy Management Systems / Supervisory Control and Data Acquisition) system based on distributed object technology, which offers the flexibility and expandability adapting those movements. In this paper, the authors introduce a prototype of the power system information delivering system, which was developed based on SCOPE architecture. This paper describes the architecture and the evaluation results of this prototype system. The power system information delivering system supplies useful power systems information such as electric power failures to the customers using Internet and distributed object technology. This system is new type of SCADA system which monitors failure of power transmission system and power distribution system with geographic information integrated way.

SU-F-J-59: Assessment of Dose Response Distribution in Individual Human Tumor

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

Yan, D; Chen, S; Krauss, D

Purpose: To fulfill precision radiotherapy via adaptive dose painting by number, voxel-by-voxel dose response or radio-sensitivity in individual human tumor needs to be determined in early treatment to guide treatment adaptation. In this study, multiple FDG PET images obtained pre- and weekly during the treatment course were utilized to determine the distribution/spectrum of dose response parameters in individual human tumors. Methods: FDG PET/CT images of 18 HN cancer patients were used in the study. Spatial parametric image of tumor metabolic ratio (dSUV) was created following voxel by voxel deformable image registration. Each voxel value in dSUV was a function ofmore » pre-treatment baseline SUV and treatment delivered dose, and used as a surrogate of tumor survival fraction (SF). Regression fitting with break points was performed using the LQ-model with tumor proliferation for the control and failure group of tumors separately. The distribution and spectrum of radiation sensitivity and growth in individual tumors were determined and evaluated. Results: Spectrum of tumor dose-sensitivity and proliferation in the controlled group was broad with α in tumor survival LQ-model from 0.17 to 0.8. It was proportional to the baseline SUV. Tlag was about 21∼25 days, and Tpot about 0.56∼1.67 days respectively. Commonly tumor voxels with high radio-sensitivity or larger α had small Tlag and Tpot. For the failure group, the radio-sensitivity α was low within 0.05 to 0.3, but did not show clear Tlag. In addition, tumor voxel radio-sensitivity could be estimated during the early treatment weeks. Conclusion: Dose response distribution with respect to radio-sensitivity and growth in individual human tumor can be determined using FDG PET imaging based tumor metabolic ratio measured in early treatment course. The discover is critical and provides a potential quantitative objective to implement tumor specific precision radiotherapy via adaptive dose painting by number.« less

Adaptive optical system for writing large holographic optical elements

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

Tyutchev, M.V.; Kalyashov, E.V.; Pavlov, A.P.

1994-11-01

This paper formulates the requirements imposed on systems for correcting the phase-difference distribution of recording waves over the field of a large-diameter photographic plate ({le}1.5 m) when writing holographic optical elements (HOEs). A technique is proposed for writing large HOEs, based on the use of an adaptive phase-correction optical system of the first type, controlled by the self-diffraction signal from a latent image. The technique is implemented by writing HOEs on photographic plates with an effective diameter of 0.7 m on As{sub 2}S{sub 3} layers. 13 refs., 4 figs.

Rain sampling device

DOEpatents

Nelson, D.A.; Tomich, S.D.; Glover, D.W.; Allen, E.V.; Hales, J.M.; Dana, M.T.

1991-05-14

The present invention constitutes a rain sampling device adapted for independent operation at locations remote from the user which allows rainfall to be sampled in accordance with any schedule desired by the user. The rain sampling device includes a mechanism for directing wet precipitation into a chamber, a chamber for temporarily holding the precipitation during the process of collection, a valve mechanism for controllably releasing samples of the precipitation from the chamber, a means for distributing the samples released from the holding chamber into vessels adapted for permanently retaining these samples, and an electrical mechanism for regulating the operation of the device. 11 figures.

Rain sampling device

DOEpatents

Nelson, Danny A.; Tomich, Stanley D.; Glover, Donald W.; Allen, Errol V.; Hales, Jeremy M.; Dana, Marshall T.

1991-01-01

The present invention constitutes a rain sampling device adapted for independent operation at locations remote from the user which allows rainfall to be sampled in accordance with any schedule desired by the user. The rain sampling device includes a mechanism for directing wet precipitation into a chamber, a chamber for temporarily holding the precipitation during the process of collection, a valve mechanism for controllably releasing samples of said precipitation from said chamber, a means for distributing the samples released from the holding chamber into vessels adapted for permanently retaining these samples, and an electrical mechanism for regulating the operation of the device.

Control - Demands mushroom as station grows

NASA Technical Reports Server (NTRS)

Szirmay, S. Z.; Blair, J.

1983-01-01

The NASA space station, which is presently in the planning stage, is to be composed of both rigid and nonrigid modules, rotating elements, and flexible appendages subjected to environmental disturbances from the earth's atmospheric gravity gradient, and magnetic field, as well as solar radiation and self-generated disturbances. Control functions, which will originally include attitude control, docking and berthing control, and system monitoring and management, will with evolving mission objectives come to encompass such control functions as articulation control, autonomous navigation, space traffic control, and large space structure control. Attention is given to the advancements in modular, distributed, and adaptive control methods, as well as system identification and hardware fault tolerance techniques, which will be required.

Demonstration of a vectorial optical field generator with adaptive close loop control.

PubMed

Chen, Jian; Kong, Lingjiang; Zhan, Qiwen

2017-12-01

We experimentally demonstrate a vectorial optical field generator (VOF-Gen) with an adaptive close loop control. The close loop control capability is illustrated with the calibration of polarization modulation of the system. To calibrate the polarization ratio modulation, we generate 45° linearly polarized beam and make it propagate through a linear analyzer whose transmission axis is orthogonal to the incident beam. For the retardation calibration, circularly polarized beam is employed and a circular polarization analyzer with the opposite chirality is placed in front of the CCD as the detector. In both cases, the close loop control automatically changes the value of the corresponding calibration parameters in the pre-set ranges to generate the phase patterns applied to the spatial light modulators and records the intensity distribution of the output beam by the CCD camera. The optimized calibration parameters are determined corresponding to the minimum total intensity in each case. Several typical kinds of vectorial optical beams are created with and without the obtained calibration parameters, and the full Stokes parameter measurements are carried out to quantitatively analyze the polarization distribution of the generated beams. The comparisons among these results clearly show that the obtained calibration parameters could remarkably improve the accuracy of the polarization modulation of the VOF-Gen, especially for generating elliptically polarized beam with large ellipticity, indicating the significance of the presented close loop in enhancing the performance of the VOF-Gen.

Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

NASA Astrophysics Data System (ADS)

Chen, Jiaxi; Li, Junmin

2018-02-01

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T-S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

Metamorphosing reef fishes avoid predator scent when choosing a home.

PubMed

Vail, Alexander L; McCormick, Mark I

2011-12-23

Most organisms possess anti-predator adaptations to reduce their risk of being consumed, but little is known of the adaptations prey employ during vulnerable life-history transitions when predation pressures can be extreme. We demonstrate the use of a transition-specific anti-predator adaptation by coral reef fishes as they metamorphose from pelagic larvae to benthic juveniles, when over half are consumed within 48 h. Our field experiment shows that naturally settling damselfish use olfactory, and most likely innate, predator recognition to avoid settling to habitat patches manipulated to emit predator odour. Settlement to patches emitting predator odour was on average 24-43% less than to control patches. Evidence strongly suggests that this avoidance of sedentary and patchily distributed predators by nocturnal settlers will gain them a survival advantage, but also lead to non-lethal predator effects: the costs of exhibiting anti-predator adaptations. Transition-specific anti-predator adaptations, such as demonstrated here, may be widespread among organisms with complex life cycles and play an important role in prey population dynamics.

Towards Internet QoS provisioning based on generic distributed QoS adaptive routing engine.

PubMed

Haikal, Amira Y; Badawy, M; Ali, Hesham A

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature.

Towards Internet QoS Provisioning Based on Generic Distributed QoS Adaptive Routing Engine

PubMed Central

Haikal, Amira Y.; Badawy, M.; Ali, Hesham A.

2014-01-01

Increasing efficiency and quality demands of modern Internet technologies drive today's network engineers to seek to provide quality of service (QoS). Internet QoS provisioning gives rise to several challenging issues. This paper introduces a generic distributed QoS adaptive routing engine (DQARE) architecture based on OSPFxQoS. The innovation of the proposed work in this paper is its undependability on the used QoS architectures and, moreover, splitting of the control strategy from data forwarding mechanisms, so we guarantee a set of absolute stable mechanisms on top of which Internet QoS can be built. DQARE architecture is furnished with three relevant traffic control schemes, namely, service differentiation, QoS routing, and traffic engineering. The main objective of this paper is to (i) provide a general configuration guideline for service differentiation, (ii) formalize the theoretical properties of different QoS routing algorithms and then introduce a QoS routing algorithm (QOPRA) based on dynamic programming technique, and (iii) propose QoS multipath forwarding (QMPF) model for paths diversity exploitation. NS2-based simulations proved the DQARE superiority in terms of delay, packet delivery ratio, throughput, and control overhead. Moreover, extensive simulations are used to compare the proposed QOPRA algorithm and QMPF model with their counterparts in the literature. PMID:25309955

Varying selection differential throughout the climatic range of Norway spruce in Central Europe.

PubMed

Kapeller, Stefan; Dieckmann, Ulf; Schueler, Silvio

2017-01-01

Predicting species distribution changes in global warming requires an understanding of how climatic constraints shape the genetic variation of adaptive traits and force local adaptations. To understand the genetic capacity of Norway spruce populations in Central Europe, we analyzed the variation in tree heights at the juvenile stage in common garden experiments established from the species' warm-dry to cold-moist distribution limits. We report the following findings: First, 47% of the total tree height variation at trial sites is attributable to the tree populations irrespective of site climate. Second, tree height variation within populations is higher at cold-moist trial sites than at warm-dry sites and higher within populations originating from cold-moist habitats than from warm-dry habitats. Third, for tree ages of 7-15 years, the variation within populations increases at cold-moist trial sites, whereas it remains constant at warm-dry sites. Fourth, tree height distributions are right-skewed at cold-moist trial sites, whereas they are nonskewed, but platykurtic at warm-dry sites. Our results suggest that in cold environments, climatic conditions impose stronger selection and probably restrict the distribution of spruce, whereas at the warm distribution limit, the species' realized niche might rather be controlled by external drivers, for example, forest insects.

Explaining spatial variability in stream habitats using both natural and management-influenced landscape predictors

Treesearch

K.J. Anlauf; D.W. Jensen; K.M. Burnett; E.A. Steel; K. Christiansen; J.C. Firman; B.E. Feist; D.P. Larsen

2011-01-01

1. The distribution and composition of in-stream habitats are reflections of landscape scale geomorphic and climatic controls. Correspondingly, Pacific salmon (Oncorhynchus spp.) are largely adapted to and constrained by the quality and complexity of those in-stream habitat conditions. The degree to which lands have been fragmented and managed can...

Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.

PubMed

Xie, Yuanlong; Tang, Xiaoqi; Song, Bao; Zhou, Xiangdong; Guo, Yixuan

2018-04-01

In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts. The proposed method directly exploits the closed-loop process data for the AFOPI controller design under unknown noise distribution and data missing probability. Firstly, the proposed method constructs the AFOPI controller tuning problem as a parameter identification problem using the modified l p norm virtual reference feedback tuning (VRFT). Then, iteratively reweighted least squares is integrated into the l p norm VRFT to give a consistent compensation solution for the AFOPI controller. The measurement noise and data dropouts are estimated and eliminated by feedback compensation periodically, so that the AFOPI controller is updated online to accommodate the time-varying operating conditions. Moreover, the convergence and stability are guaranteed by mathematical analysis. Finally, the effectiveness of the proposed method is demonstrated both on simulations and experiments implemented on a practical PMSM servo system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Re-examination of sea lamprey control policies for the St. Marys River: Completion of an adaptive management cycle

USGS Publications Warehouse

Jones, Michael L.; Brenden, Travis O.; Irwin, Brian J.

2015-01-01

The St. Marys River (SMR) historically has been a major producer of sea lampreys (Petromyzon marinus) in the Laurentian Great Lakes. In the early 2000s, a decision analysis (DA) project was conducted to evaluate sea lamprey control policies for the SMR; this project suggested that an integrated policy of trapping, sterile male releases, and Bayluscide treatment was the most cost-effective policy. Further, it concluded that formal assessment of larval sea lamprey abundance and distribution in the SMR would be valuable for future evaluation of control strategies. We updated this earlier analysis, adding information from annual larval assessments conducted since 1999 and evaluating additional control policies. Bayluscide treatments continued to be critical for sea lamprey control, but high recruitment compensation minimized the effectiveness of trapping and sterile male release under current feasible ranges. Because Bayluscide control is costly, development of strategies to enhance trapping success remains a priority. This study illustrates benefits of an adaptive management cycle, wherein models inform decisions, are updated based on learning achieved from those decisions, and ultimately inform future decisions.

Distributed memory approaches for robotic neural controllers

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1990-01-01

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Modeling Power Systems as Complex Adaptive Systems

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

Chassin, David P.; Malard, Joel M.; Posse, Christian

2004-12-30

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We reviewmore » and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.« less

The Raid distributed database system

NASA Technical Reports Server (NTRS)

Bhargava, Bharat; Riedl, John

1989-01-01

Raid, a robust and adaptable distributed database system for transaction processing (TP), is described. Raid is a message-passing system, with server processes on each site to manage concurrent processing, consistent replicated copies during site failures, and atomic distributed commitment. A high-level layered communications package provides a clean location-independent interface between servers. The latest design of the package delivers messages via shared memory in a configuration with several servers linked into a single process. Raid provides the infrastructure to investigate various methods for supporting reliable distributed TP. Measurements on TP and server CPU time are presented, along with data from experiments on communications software, consistent replicated copy control during site failures, and concurrent distributed checkpointing. A software tool for evaluating the implementation of TP algorithms in an operating-system kernel is proposed.

Distributed fault-tolerant time-varying formation control for high-order linear multi-agent systems with actuator failures.

PubMed

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-11-01

This paper investigates the fault-tolerant time-varying formation control problems for high-order linear multi-agent systems in the presence of actuator failures. Firstly, a fully distributed formation control protocol is presented to compensate for the influences of both bias fault and loss of effectiveness fault. Using the adaptive online updating strategies, no global knowledge about the communication topology is required and the bounds of actuator failures can be unknown. Then an algorithm is proposed to determine the control parameters of the fault-tolerant formation protocol, where the time-varying formation feasible conditions and an approach to expand the feasible formation set are given. Furthermore, the stability of the proposed algorithm is proven based on the Lyapunov-like theory. Finally, two simulation examples are given to demonstrate the effectiveness of the theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Simulation on an optimal combustion control strategy for 3-D temperature distributions in tangentially pc-fired utility boiler furnaces.

PubMed

Wang, Xi-fen; Zhou, Huai-chun

2005-01-01

The control of 3-D temperature distribution in a utility boiler furnace is essential for the safe, economic and clean operation of pc-fired furnace with multi-burner system. The development of the visualization of 3-D temperature distributions in pc-fired furnaces makes it possible for a new combustion control strategy directly with the furnace temperature as its goal to improve the control quality for the combustion processes. Studied in this paper is such a new strategy that the whole furnace is divided into several parts in the vertical direction, and the average temperature and its bias from the center in every cross section can be extracted from the visualization results of the 3-D temperature distributions. In the simulation stage, a computational fluid dynamics (CFD) code served to calculate the 3-D temperature distributions in a furnace, then a linear model was set up to relate the features of the temperature distributions with the input of the combustion processes, such as the flow rates of fuel and air fed into the furnaces through all the burners. The adaptive genetic algorithm was adopted to find the optimal combination of the whole input parameters which ensure to form an optimal 3-D temperature field in the furnace desired for the operation of boiler. Simulation results showed that the strategy could soon find the factors making the temperature distribution apart from the optimal state and give correct adjusting suggestions.

Mechanosensitive control of plant growth: bearing the load, sensing, transducing, and responding

PubMed Central

Moulia, Bruno; Coutand, Catherine; Julien, Jean-Louis

2015-01-01

As land plants grow and develop, they encounter complex mechanical challenges, especially from winds and turgor pressure. Mechanosensitive control over growth and morphogenesis is an adaptive trait, reducing the risks of breakage or explosion. This control has been mostly studied through experiments with artificial mechanical loads, often focusing on cellular or molecular mechanotransduction pathway. However, some important aspects of mechanosensing are often neglected. (i) What are the mechanical characteristics of different loads and how are loads distributed within different organs? (ii) What is the relevant mechanical stimulus in the cell? Is it stress, strain, or energy? (iii) How do mechanosensing cells signal to meristematic cells? Without answers to these questions we cannot make progress analyzing the mechanobiological effects of plant size, plant shape, tissue distribution and stiffness, or the magnitude of stimuli. This situation is rapidly changing however, as systems mechanobiology is being developed, using specific biomechanical and/or mechanobiological models. These models are instrumental in comparing loads and responses between experiments and make it possible to quantitatively test biological hypotheses describing the mechanotransduction networks. This review is designed for a general plant science audience and aims to help biologists master the models they need for mechanobiological studies. Analysis and modeling is broken down into four steps looking at how the structure bears the load, how the distributed load is sensed, how the mechanical signal is transduced, and then how the plant responds through growth. Throughout, two examples of adaptive responses are used to illustrate this approach: the thigmorphogenetic syndrome of plant shoots bending and the mechanosensitive control of shoot apical meristem (SAM) morphogenesis. Overall this should provide a generic understanding of systems mechanobiology at work. PMID:25755656

Controls for space structures

NASA Astrophysics Data System (ADS)

Balas, Mark

1991-11-01

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control.

Controls for space structures

NASA Technical Reports Server (NTRS)

Balas, Mark

1991-01-01

Assembly and operation of large space structures (LSS) in orbit will require robot-assisted docking and berthing of partially-assembled structures. These operations require new solutions to the problems of controls. This is true because of large transient and persistent disturbances, controller-structure interaction with unmodeled modes, poorly known structure parameters, slow actuator/sensor dynamical behavior, and excitation of nonlinear structure vibrations during control and assembly. For on-orbit assembly, controllers must start with finite element models of LSS and adapt on line to the best operating points, without compromising stability. This is not easy to do, since there are often unmodeled dynamic interactions between the controller and the structure. The indirect adaptive controllers are based on parameter estimation. Due to the large number of modes in LSS, this approach leads to very high-order control schemes with consequent poor stability and performance. In contrast, direct model reference adaptive controllers operate to force the LSS to track the desirable behavior of a chosen model. These schemes produce simple control algorithms which are easy to implement on line. One problem with their use for LSS has been that the model must be the same dimension as the LSS - i.e., quite large. A control theory based on the command generator tracker (CGT) ideas of Sobel, Mabins, Kaufman and Wen, Balas to obtain very low-order models based on adaptive algorithms was developed. Closed-loop stability for both finite element models and distributed parameter models of LSS was proved. In addition, successful numerical simulations on several LSS databases were obtained. An adaptive controller based on our theory was also implemented on a flexible robotic manipulator at Martin Marietta Astronautics. Computation schemes for controller-structure interaction with unmodeled modes, the residual mode filters or RMF, were developed. The RMF theory was modified to compensate slow actuator/sensor dynamics. These new ideas are being applied to LSS simulations to demonstrate the ease with which one can incorporate slow actuator/sensor effects into our design. It was also shown that residual mode filter compensation can be modified for small nonlinearities to produce exponentially stable closed-loop control. A theory for disturbance accommodating controllers based on reduced order models of structures was developed, and stability results for these controllers in closed-loop with large-scale finite element models of structures were obtained.

An adaptive wing for a small-aircraft application with a configuration of fibre Bragg grating sensors

NASA Astrophysics Data System (ADS)

Mieloszyk, M.; Krawczuk, M.; Zak, A.; Ostachowicz, W.

2010-08-01

In this paper a concept of an adaptive wing for small-aircraft applications with an array of fibre Bragg grating (FBG) sensors has been presented and discussed. In this concept the shape of the wing can be controlled and altered thanks to the wing design and the use of integrated shape memory alloy actuators. The concept has been tested numerically by the use of the finite element method. For numerical calculations the commercial finite element package ABAQUS® has been employed. A finite element model of the wing has been prepared in order to estimate the values of the wing twisting angles and distributions of the twist for various activation scenarios. Based on the results of numerical analysis the locations and numbers of the FBG sensors have also been determined. The results of numerical calculations obtained by the authors confirmed the usefulness of the assumed wing control strategy. Based on them and the concept developed of the adaptive wing, a wing demonstration stand has been designed and built. The stand has been used to verify experimentally the performance of the adaptive wing and the usefulness of the FBG sensors for evaluation of the wing condition.

Electron gun controlled smart structure

DOEpatents

Martin, Jeffrey W.; Main, John Alan; Redmond, James M.; Henson, Tammy D.; Watson, Robert D.

2001-01-01

Disclosed is a method and system for actively controlling the shape of a sheet of electroactive material; the system comprising: one or more electrodes attached to the frontside of the electroactive sheet; a charged particle generator, disposed so as to direct a beam of charged particles (e.g. electrons) onto the electrode; a conductive substrate attached to the backside of the sheet; and a power supply electrically connected to the conductive substrate; whereby the sheet changes its shape in response to an electric field created across the sheet by an accumulation of electric charge within the electrode(s), relative to a potential applied to the conductive substrate. Use of multiple electrodes distributed across on the frontside ensures a uniform distribution of the charge with a single point of e-beam incidence, thereby greatly simplifying the beam scanning algorithm and raster control electronics, and reducing the problems associated with "blooming". By placing a distribution of electrodes over the front surface of a piezoelectric film (or other electroactive material), this arrangement enables improved control over the distribution of surface electric charges (e.g. electrons) by creating uniform (and possibly different) charge distributions within each individual electrode. Removal or deposition of net electric charge can be affected by controlling the secondary electron yield through manipulation of the backside electric potential with the power supply. The system can be used for actively controlling the shape of space-based deployable optics, such as adaptive mirrors and inflatable antennae.

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

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

Lu, Dan; Ricciuto, Daniel; Walker, Anthony

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

DOE PAGES

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; ...

2017-02-22

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

Distributed cerebellar plasticity implements generalized multiple-scale memory components in real-robot sensorimotor tasks.

PubMed

Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Ferrigno, Giancarlo; D'Angelo, Egidio; Pedrocchi, Alessandra

2015-01-01

The cerebellum plays a crucial role in motor learning and it acts as a predictive controller. Modeling it and embedding it into sensorimotor tasks allows us to create functional links between plasticity mechanisms, neural circuits and behavioral learning. Moreover, if applied to real-time control of a neurorobot, the cerebellar model has to deal with a real noisy and changing environment, thus showing its robustness and effectiveness in learning. A biologically inspired cerebellar model with distributed plasticity, both at cortical and nuclear sites, has been used. Two cerebellum-mediated paradigms have been designed: an associative Pavlovian task and a vestibulo-ocular reflex, with multiple sessions of acquisition and extinction and with different stimuli and perturbation patterns. The cerebellar controller succeeded to generate conditioned responses and finely tuned eye movement compensation, thus reproducing human-like behaviors. Through a productive plasticity transfer from cortical to nuclear sites, the distributed cerebellar controller showed in both tasks the capability to optimize learning on multiple time-scales, to store motor memory and to effectively adapt to dynamic ranges of stimuli.

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew J.; Roychoudhury, Indranil

2012-01-01

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.

Customizing the JPL Multimission Ground Data System: Lessons learned

NASA Technical Reports Server (NTRS)

Murphy, Susan C.; Louie, John J.; Guerrero, Ana Maria; Hurley, Daniel; Flora-Adams, Dana

1994-01-01

The Multimission Ground Data System (MGDS) at NASA's Jet Propulsion Laboratory has brought improvements and new technologies to mission operations. It was designed as a generic data system to meet the needs of multiple missions and avoid re-inventing capabilities for each new mission and thus reduce costs. It is based on adaptable tools that can be customized to support different missions and operations scenarios. The MGDS is based on a distributed client/server architecture, with powerful Unix workstations, incorporating standards and open system architectures. The distributed architecture allows remote operations and user science data exchange, while also providing capabilities for centralized ground system monitor and control. The MGDS has proved its capabilities in supporting multiple large-class missions simultaneously, including the Voyager, Galileo, Magellan, Ulysses, and Mars Observer missions. The Operations Engineering Lab (OEL) at JPL has been leading Customer Adaptation Training (CAT) teams for adapting and customizing MGDS for the various operations and engineering teams. These CAT teams have typically consisted of only a few engineers who are familiar with operations and with the MGDS software and architecture. Our experience has provided a unique opportunity to work directly with the spacecraft and instrument operations teams and understand their requirements and how the MGDS can be adapted and customized to minimize their operations costs. As part of this work, we have developed workstation configurations, automation tools, and integrated user interfaces at minimal cost that have significantly improved productivity. We have also proved that these customized data systems are most successful if they are focused on the people and the tasks they perform and if they are based upon user confidence in the development team resulting from daily interactions. This paper will describe lessons learned in adapting JPL's MGDS to fly the Voyager, Galileo, and Mars Observer missions. We will explain how powerful, existing ground data systems can be adapted and packaged in a cost effective way for operations of small and large planetary missions. We will also describe how the MGDS was adapted to support operations within the Galileo Spacecraft Testbed. The Galileo testbed provided a unique opportunity to adapt MGDS to support command and control operations for a small autonomous operations team of a handful of engineers flying the Galileo Spacecraft flight system model.

A two-stage predictive model to simultaneous control of trihalomethanes in water treatment plants and distribution systems: adaptability to treatment processes.

PubMed

Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis

2017-10-01

The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance <17%). The new model was applied to three different supply systems with different treatment processes and different characteristics. Acceptable predictions were obtained in the three distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.

Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters.

PubMed

Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline; Keller, Peter; Pelot, Ronald

2008-05-01

This paper examines the use of exploratory spatial analysis for identifying hotspots of shipping-based oil pollution in the Pacific Region of Canada's Exclusive Economic Zone. It makes use of data collected from fiscal years 1997/1998 to 2005/2006 by the National Aerial Surveillance Program, the primary tool for monitoring and enforcing the provisions imposed by MARPOL 73/78. First, we present oil spill data as points in a "dot map" relative to coastlines, harbors and the aerial surveillance distribution. Then, we explore the intensity of oil spill events using the Quadrat Count method, and the Kernel Density Estimation methods with both fixed and adaptive bandwidths. We found that oil spill hotspots where more clearly defined using Kernel Density Estimation with an adaptive bandwidth, probably because of the "clustered" distribution of oil spill occurrences. Finally, we discuss the importance of standardizing oil spill data by controlling for surveillance effort to provide a better understanding of the distribution of illegal oil spills, and how these results can ultimately benefit a monitoring program.

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2008-01-01

A new approach for distribution of grid points on the surface and in the volume has been developed and implemented in the NASA unstructured grid generation code VGRID. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Advanced Unstructured Grid Generation for Complex Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar

2010-01-01

A new approach for distribution of grid points on the surface and in the volume has been developed. In addition to the point and line sources of prior work, the new approach utilizes surface and volume sources for automatic curvature-based grid sizing and convenient point distribution in the volume. A new exponential growth function produces smoother and more efficient grids and provides superior control over distribution of grid points in the field. All types of sources support anisotropic grid stretching which not only improves the grid economy but also provides more accurate solutions for certain aerodynamic applications. The new approach does not require a three-dimensional background grid as in the previous methods. Instead, it makes use of an efficient bounding-box auxiliary medium for storing grid parameters defined by surface sources. The new approach is less memory-intensive and more efficient computationally. The grids generated with the new method either eliminate the need for adaptive grid refinement for certain class of problems or provide high quality initial grids that would enhance the performance of many adaptation methods.

Adaptive Multi-Layer LMS Controller Design and Application to Active Vibration Suppression on a Truss and Proposed Impact Analysis Technique

NASA Technical Reports Server (NTRS)

Barney, Timothy A.; Shin, Y. S.; Agrawal, B. N.

2001-01-01

This research develops an adaptive controller that actively suppresses a single frequency disturbance source at a remote position and tests the system on the NPS Space Truss. The experimental results are then compared to those predicted by an ANSYS finite element model. The NPS space truss is a 3.7-meter long truss that simulates a space-borne appendage with sensitive equipment mounted at its extremities. One of two installed piezoelectric actuators and an Adaptive Multi-Layer LMS control law were used to effectively eliminate an axial component of the vibrations induced by a linear proof mass actuator mounted at one end of the truss. Experimental and analytical results both demonstrate reductions to the level of system noise. Vibration reductions in excess of 50dB were obtained through experimentation and over 100dB using ANSYS, demonstrating the ability to model this system with a finite element model. This report also proposes a method to use distributed quartz accelerometers to evaluate the location, direction, and energy of impacts on the NPS space truss using the dSPACE data acquisition and processing system to capture the structural response and compare it to known reference Signals.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Flow-rate control for managing communications in tracking and surveillance networks

NASA Astrophysics Data System (ADS)

Miller, Scott A.; Chong, Edwin K. P.

2007-09-01

This paper describes a primal-dual distributed algorithm for managing communications in a bandwidth-limited sensor network for tracking and surveillance. The algorithm possesses some scale-invariance properties and adaptive gains that make it more practical for applications such as tracking where the conditions change over time. A simulation study comparing this algorithm with a priority-queue-based approach in a network tracking scenario shows significant improvement in the resulting track quality when using flow control to manage communications.

Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

NASA Technical Reports Server (NTRS)

Aucoin, B. M.; Heller, R. P.

1990-01-01

An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

Distributed reservation control protocols for random access broadcasting channels

NASA Technical Reports Server (NTRS)

Greene, E. P.; Ephremides, A.

1981-01-01

Attention is given to a communication network consisting of an arbitrary number of nodes which can communicate with each other via a time-division multiple access (TDMA) broadcast channel. The reported investigation is concerned with the development of efficient distributed multiple access protocols for traffic consisting primarily of single packet messages in a datagram mode of operation. The motivation for the design of the protocols came from the consideration of efficient multiple access utilization of moderate to high bandwidth (4-40 Mbit/s capacity) communication satellite channels used for the transmission of short (1000-10,000 bits) fixed length packets. Under these circumstances, the ratio of roundtrip propagation time to packet transmission time is between 100 to 10,000. It is shown how a TDMA channel can be adaptively shared by datagram traffic and constant bandwidth users such as in digital voice applications. The distributed reservation control protocols described are a hybrid between contention and reservation protocols.

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

NASA Technical Reports Server (NTRS)

Ong, James; Remolina, Emilio; Prompt, Axel; Robinson, Peter; Sweet, Adam; Nishikawa, David

2015-01-01

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE). an object-oriented toolkit for building distributed applications.

Empirical evidence for multi-scaled controls on wildfire size distributions in California

NASA Astrophysics Data System (ADS)

Povak, N.; Hessburg, P. F., Sr.; Salter, R. B.

2014-12-01

Ecological theory asserts that regional wildfire size distributions are examples of self-organized critical (SOC) systems. Controls on SOC event-size distributions by virtue are purely endogenous to the system and include the (1) frequency and pattern of ignitions, (2) distribution and size of prior fires, and (3) lagged successional patterns after fires. However, recent work has shown that the largest wildfires often result from extreme climatic events, and that patterns of vegetation and topography may help constrain local fire spread, calling into question the SOC model's simplicity. Using an atlas of >12,000 California wildfires (1950-2012) and maximum likelihood estimation (MLE), we fit four different power-law models and broken-stick regressions to fire-size distributions across 16 Bailey's ecoregions. Comparisons among empirical fire size distributions across ecoregions indicated that most ecoregion's fire-size distributions were significantly different, suggesting that broad-scale top-down controls differed among ecoregions. One-parameter power-law models consistently fit a middle range of fire sizes (~100 to 10000 ha) across most ecoregions, but did not fit to larger and smaller fire sizes. We fit the same four power-law models to patch size distributions of aspect, slope, and curvature topographies and found that the power-law models fit to a similar middle range of topography patch sizes. These results suggested that empirical evidence may exist for topographic controls on fire sizes. To test this, we used neutral landscape modeling techniques to determine if observed fire edges corresponded with aspect breaks more often than expected by random. We found significant differences between the empirical and neutral models for some ecoregions, particularly within the middle range of fire sizes. Our results, combined with other recent work, suggest that controls on ecoregional fire size distributions are multi-scaled and likely are not purely SOC. California wildfire ecosystems appear to be adaptive, governed by stationary and non-stationary controls, which may be either exogenous or endogenous to the system.

Adapting nematode-based biological control systems to North American populations of Sirex noctilio

Treesearch

David W. Williams; Victor C. Mastro

2011-01-01

The European woodwasp, Sirex noctilio, was found in Oswego County, NY, in 2004. During the past 6 years, surveys have revealed that it is distributed over a wide area of eastern North America. Because S. noctilio kills relatively healthy trees, it poses a serious threat to pine forests and plantations in the United States and...

Sleep Disturbances, Behavioural Problems and Adaptive Skills in Children with Down's Syndrome

ERIC Educational Resources Information Center

Kelmanson, Igor A.

2017-01-01

The study was performed in St. Petersburg in 2015 and comprised 34 children with diagnosed Down's syndrome (DS) aged 9-15 (mean 11) years (17 boys, 17 girls) who attended special schools. Control group was made up of 34 clinically healthy normal intelligence schoolchildren matched for age, sex and geographical distribution. The mothers were…

Distribution history and climatic controls of the Late Miocene Pikermian chronofauna.

PubMed

Eronen, Jussi T; Ataabadi, Majid Mirzaie; Micheels, Arne; Karme, Aleksis; Bernor, Raymond L; Fortelius, Mikael

2009-07-21

The Late Miocene development of faunas and environments in western Eurasia is well known, but the climatic and environmental processes that controlled its details are incompletely understood. Here we map the rise and fall of the classic Pikermian fossil mammal chronofauna between 12 and 4.2 Ma, using genus-level faunal similarity between localities. To directly relate land mammal community evolution to environmental change, we use the hypsodonty paleoprecipitation proxy and paleoclimate modeling. The geographic distribution of faunal similarity and paleoprecipitation in successive timeslices shows the development of the open biome that favored the evolution and spread of the open-habitat adapted large mammal lineages. In the climate model run, this corresponds to a decrease in precipitation over its core area south of the Paratethys Sea. The process began in the latest Middle Miocene and climaxed in the medial Late Miocene, about 7-8 million years ago. The geographic range of the Pikermian chronofauna contracted in the latest Miocene, a time of increasing summer drought and regional differentiation of habitats in Eastern Europe and Southwestern Asia. Its demise at the Miocene-Pliocene boundary coincides with an environmental reversal toward increased humidity and forestation, changes inevitably detrimental to open-adapted, wide-ranging large mammals.

Adaptive control system having hedge unit and related apparatus and methods

NASA Technical Reports Server (NTRS)

Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

2003-01-01

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference.

PubMed

Corrêa, A M; Teodoro, P E; Gonçalves, M C; Barroso, L M A; Nascimento, M; Santos, A; Torres, F E

2016-04-27

This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition

PubMed Central

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-01-01

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition. PMID:28467371

A Fast, Efficient Domain Adaptation Technique for Cross-Domain Electroencephalography(EEG)-Based Emotion Recognition.

PubMed

Chai, Xin; Wang, Qisong; Zhao, Yongping; Li, Yongqiang; Liu, Dan; Liu, Xin; Bai, Ou

2017-05-03

Electroencephalography (EEG)-based emotion recognition is an important element in psychiatric health diagnosis for patients. However, the underlying EEG sensor signals are always non-stationary if they are sampled from different experimental sessions or subjects. This results in the deterioration of the classification performance. Domain adaptation methods offer an effective way to reduce the discrepancy of marginal distribution. However, for EEG sensor signals, both marginal and conditional distributions may be mismatched. In addition, the existing domain adaptation strategies always require a high level of additional computation. To address this problem, a novel strategy named adaptive subspace feature matching (ASFM) is proposed in this paper in order to integrate both the marginal and conditional distributions within a unified framework (without any labeled samples from target subjects). Specifically, we develop a linear transformation function which matches the marginal distributions of the source and target subspaces without a regularization term. This significantly decreases the time complexity of our domain adaptation procedure. As a result, both marginal and conditional distribution discrepancies between the source domain and unlabeled target domain can be reduced, and logistic regression (LR) can be applied to the new source domain in order to train a classifier for use in the target domain, since the aligned source domain follows a distribution which is similar to that of the target domain. We compare our ASFM method with six typical approaches using a public EEG dataset with three affective states: positive, neutral, and negative. Both offline and online evaluations were performed. The subject-to-subject offline experimental results demonstrate that our component achieves a mean accuracy and standard deviation of 80.46% and 6.84%, respectively, as compared with a state-of-the-art method, the subspace alignment auto-encoder (SAAE), which achieves values of 77.88% and 7.33% on average, respectively. For the online analysis, the average classification accuracy and standard deviation of ASFM in the subject-to-subject evaluation for all the 15 subjects in a dataset was 75.11% and 7.65%, respectively, gaining a significant performance improvement compared to the best baseline LR which achieves 56.38% and 7.48%, respectively. The experimental results confirm the effectiveness of the proposed method relative to state-of-the-art methods. Moreover, computational efficiency of the proposed ASFM method is much better than standard domain adaptation; if the numbers of training samples and test samples are controlled within certain range, it is suitable for real-time classification. It can be concluded that ASFM is a useful and effective tool for decreasing domain discrepancy and reducing performance degradation across subjects and sessions in the field of EEG-based emotion recognition.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Enhanced High Performance Power Compensation Methodology by IPFC Using PIGBT-IDVR

PubMed Central

Arumugom, Subramanian; Rajaram, Marimuthu

2015-01-01

Currently, power systems are involuntarily controlled without high speed control and are frequently initiated, therefore resulting in a slow process when compared with static electronic devices. Among various power interruptions in power supply systems, voltage dips play a central role in causing disruption. The dynamic voltage restorer (DVR) is a process based on voltage control that compensates for line transients in the distributed system. To overcome these issues and to achieve a higher speed, a new methodology called the Parallel IGBT-Based Interline Dynamic Voltage Restorer (PIGBT-IDVR) method has been proposed, which mainly spotlights the dynamic processing of energy reloads in common dc-linked energy storage with less adaptive transition. The interline power flow controller (IPFC) scheme has been employed to manage the power transmission between the lines and the restorer method for controlling the reactive power in the individual lines. By employing the proposed methodology, the failure of a distributed system has been avoided and provides better performance than the existing methodologies. PMID:26613101

Active control of the spatial MRI phase distribution with optimal control theory

NASA Astrophysics Data System (ADS)

Lefebvre, Pauline M.; Van Reeth, Eric; Ratiney, Hélène; Beuf, Olivier; Brusseau, Elisabeth; Lambert, Simon A.; Glaser, Steffen J.; Sugny, Dominique; Grenier, Denis; Tse Ve Koon, Kevin

2017-08-01

This paper investigates the use of Optimal Control (OC) theory to design Radio-Frequency (RF) pulses that actively control the spatial distribution of the MRI magnetization phase. The RF pulses are generated through the application of the Pontryagin Maximum Principle and optimized so that the resulting transverse magnetization reproduces various non-trivial and spatial phase patterns. Two different phase patterns are defined and the resulting optimal pulses are tested both numerically with the ODIN MRI simulator and experimentally with an agar gel phantom on a 4.7 T small-animal MR scanner. Phase images obtained in simulations and experiments are both consistent with the defined phase patterns. A practical application of phase control with OC-designed pulses is also presented, with the generation of RF pulses adapted for a Magnetic Resonance Elastography experiment. This study demonstrates the possibility to use OC-designed RF pulses to encode information in the magnetization phase and could have applications in MRI sequences using phase images.

ITMS: Individualized Teaching Material System: Adaptive Integration of Web Pages Distributed in Some Servers.

ERIC Educational Resources Information Center

Mitsuhara, Hiroyuki; Kurose, Yoshinobu; Ochi, Youji; Yano, Yoneo

The authors developed a Web-based Adaptive Educational System (Web-based AES) named ITMS (Individualized Teaching Material System). ITMS adaptively integrates knowledge on the distributed Web pages and generates individualized teaching material that has various contents. ITMS also presumes the learners' knowledge levels from the states of their…

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.

A Weibull distribution accrual failure detector for cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Dong, Jian; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing.

Local climatic adaptation in a widespread microorganism.

PubMed

Leducq, Jean-Baptiste; Charron, Guillaume; Samani, Pedram; Dubé, Alexandre K; Sylvester, Kayla; James, Brielle; Almeida, Pedro; Sampaio, José Paulo; Hittinger, Chris Todd; Bell, Graham; Landry, Christian R

2014-02-22

Exploring the ability of organisms to locally adapt is critical for determining the outcome of rapid climate changes, yet few studies have addressed this question in microorganisms. We investigated the role of a heterogeneous climate on adaptation of North American populations of the wild yeast Saccharomyces paradoxus. We found abundant among-strain variation for fitness components across a range of temperatures, but this variation was only partially explained by climatic variation in the distribution area. Most of fitness variation was explained by the divergence of genetically distinct groups, distributed along a north-south cline, suggesting that these groups have adapted to distinct climatic conditions. Within-group fitness components were correlated with climatic conditions, illustrating that even ubiquitous microorganisms locally adapt and harbour standing genetic variation for climate-related traits. Our results suggest that global climatic changes could lead to adaptation to new conditions within groups, or changes in their geographical distributions.

Sparse distributed memory overview

NASA Technical Reports Server (NTRS)

Raugh, Mike

1990-01-01

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists.

PubMed

Neal, Craig M; Hunter, Angus M; Brennan, Lorraine; O'Sullivan, Aifric; Hamilton, D Lee; De Vito, Giuseppe; Galloway, Stuart D R

2013-02-15

This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.

Impact Assessment of Pine Wilt Disease Using the Species Distribution Model and the CLIMEX Model

NASA Astrophysics Data System (ADS)

KIM, J. U.; Jung, H.

2016-12-01

The plant disease triangle consists of the host plant, pathogen and environment, but their interaction has not been considered in climate change adaptation policy. Our objectives are to predict the changes of a coniferous forest, pine wood nematodes (Bursaphelenchus xylophilus) and pine sawyer beetles (Monochamus spp.), which is a cause of pine wilt disease in the Republic of Korea. We analyzed the impact of pine wilt disease on climate change by using the species distribution model (SDM) and the CLIMEX model. Area of coniferous forest will decline and move to northern and high-altitude area. But pine wood nematodes and pine sawyer beetles are going to spread because they are going to be in a more favorable environment in the future. Coniferous forests are expected to have high vulnerability because of the decrease in area and the increase in the risk of pine wilt disease. Such changes to forest ecosystems will greatly affect climate change in the future. If effective and appropriate prevention and control policies are not implemented, coniferous forests will be severely damaged. An adaptation policy should be created in order to protect coniferous forests from the viewpoint of biodiversity. Thus we need to consider the impact assessment of climate change for establishing an effective adaptation policy. The impact assessment of pine wilt disease using a plant disease triangle drew suitable results to support climate change adaptation policy.

Control and Communication for a Secure and Reconfigurable Power Distribution System

NASA Astrophysics Data System (ADS)

Giacomoni, Anthony Michael

A major transformation is taking place throughout the electric power industry to overlay existing electric infrastructure with advanced sensing, communications, and control system technologies. This transformation to a smart grid promises to enhance system efficiency, increase system reliability, support the electrification of transportation, and provide customers with greater control over their electricity consumption. Upgrading control and communication systems for the end-to-end electric power grid, however, will present many new security challenges that must be dealt with before extensive deployment and implementation of these technologies can begin. In this dissertation, a comprehensive systems approach is taken to minimize and prevent cyber-physical disturbances to electric power distribution systems using sensing, communications, and control system technologies. To accomplish this task, an intelligent distributed secure control (IDSC) architecture is presented and validated in silico for distribution systems to provide greater adaptive protection, with the ability to proactively reconfigure, and rapidly respond to disturbances. Detailed descriptions of functionalities at each layer of the architecture as well as the whole system are provided. To compare the performance of the IDSC architecture with that of other control architectures, an original simulation methodology is developed. The simulation model integrates aspects of cyber-physical security, dynamic price and demand response, sensing, communications, intermittent distributed energy resources (DERs), and dynamic optimization and reconfiguration. Applying this comprehensive systems approach, performance results for the IEEE 123 node test feeder are simulated and analyzed. The results show the trade-offs between system reliability, operational constraints, and costs for several control architectures and optimization algorithms. Additional simulation results are also provided. In particular, the advantages of an IDSC architecture are highlighted when an intermittent DER is present on the system.

Adaptive control for solar energy based DC microgrid system development

NASA Astrophysics Data System (ADS)

Zhang, Qinhao

During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)'s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed.

Temporal sampling, resetting, and adaptation orchestrate gradient sensing in sperm

PubMed Central

Alvarez, Luis; Seifert, Reinhard; Gregor, Ingo; Jäckle, Oliver; Beyermann, Michael; Krause, Eberhard

2012-01-01

Sperm, navigating in a chemical gradient, are exposed to a periodic stream of chemoattractant molecules. The periodic stimulation entrains Ca2+ oscillations that control looping steering responses. It is not known how sperm sample chemoattractant molecules during periodic stimulation and adjust their sensitivity. We report that sea urchin sperm sampled molecules for 0.2–0.6 s before a Ca2+ response was produced. Additional molecules delivered during a Ca2+ response reset the cell by causing a pronounced Ca2+ drop that terminated the response; this reset was followed by a new Ca2+ rise. After stimulation, sperm adapted their sensitivity following the Weber–Fechner law. Taking into account the single-molecule sensitivity, we estimate that sperm can register a minimal gradient of 0.8 fM/µm and be attracted from as far away as 4.7 mm. Many microorganisms sense stimulus gradients along periodic paths to translate a spatial distribution of the stimulus into a temporal pattern of the cell response. Orchestration of temporal sampling, resetting, and adaptation might control gradient sensing in such organisms as well. PMID:22986497

Temporal sampling, resetting, and adaptation orchestrate gradient sensing in sperm.

PubMed

Kashikar, Nachiket D; Alvarez, Luis; Seifert, Reinhard; Gregor, Ingo; Jäckle, Oliver; Beyermann, Michael; Krause, Eberhard; Kaupp, U Benjamin

2012-09-17

Sperm, navigating in a chemical gradient, are exposed to a periodic stream of chemoattractant molecules. The periodic stimulation entrains Ca(2+) oscillations that control looping steering responses. It is not known how sperm sample chemoattractant molecules during periodic stimulation and adjust their sensitivity. We report that sea urchin sperm sampled molecules for 0.2-0.6 s before a Ca(2+) response was produced. Additional molecules delivered during a Ca(2+) response reset the cell by causing a pronounced Ca(2+) drop that terminated the response; this reset was followed by a new Ca(2+) rise. After stimulation, sperm adapted their sensitivity following the Weber-Fechner law. Taking into account the single-molecule sensitivity, we estimate that sperm can register a minimal gradient of 0.8 fM/µm and be attracted from as far away as 4.7 mm. Many microorganisms sense stimulus gradients along periodic paths to translate a spatial distribution of the stimulus into a temporal pattern of the cell response. Orchestration of temporal sampling, resetting, and adaptation might control gradient sensing in such organisms as well.

A collection of Australian Drosophila datasets on climate adaptation and species distributions.

PubMed

Hangartner, Sandra B; Hoffmann, Ary A; Smith, Ailie; Griffin, Philippa C

2015-11-24

The Australian Drosophila Ecology and Evolution Resource (ADEER) collates Australian datasets on drosophilid flies, which are aimed at investigating questions around climate adaptation, species distribution limits and population genetics. Australian drosophilid species are diverse in climatic tolerance, geographic distribution and behaviour. Many species are restricted to the tropics, a few are temperate specialists, and some have broad distributions across climatic regions. Whereas some species show adaptability to climate changes through genetic and plastic changes, other species have limited adaptive capacity. This knowledge has been used to identify traits and genetic polymorphisms involved in climate change adaptation and build predictive models of responses to climate change. ADEER brings together 103 datasets from 39 studies published between 1982-2013 in a single online resource. All datasets can be downloaded freely in full, along with maps and other visualisations. These historical datasets are preserved for future studies, which will be especially useful for assessing climate-related changes over time.

Stress reactivity, condition, and foraging behavior in zebra finches: effects on boldness, exploration, and sociality.

PubMed

Crino, O L; Buchanan, Katherine L; Trompf, Larissa; Mainwaring, Mark C; Griffith, Simon C

2017-04-01

The arid and semi-arid zones of Australia are characterized by highly variable and unpredictable environmental conditions which affect resources for flora and fauna. Environments which are highly unpredictable in terms of both resource access and distribution are likely to select for a variety of adaptive behavioral strategies, intrinsically linked to the physiological control of behavior. How unpredictable resource distribution has affected the coevolution of behavioral strategies and physiology has rarely been quantified, particularly not in Australian birds. We used a captive population of wild-derived zebra finches to test the relationships between behavioral strategies relating to food access and physiological responses to stress and body condition. We found that individuals that were in poorer body condition and had higher peak corticosterone levels entered baited feeders earlier in the trapping sequence of birds within the colony. We also found that individuals in poorer body condition fed in smaller social groups. Our data show that the foraging decisions which individuals make represent not only a trade-off between food access and risk of exposure, but their underlying physiological response to stress. Our data also suggest fundamental links between social networks and physiological parameters, which largely remain untested. These data demonstrate the fundamental importance of physiological mechanisms in controlling adaptive behavioral strategies and the dynamic interplay between physiological control of behavior and life-history evolution. Copyright © 2016 Elsevier Inc. All rights reserved.

ISIS and META projects

NASA Technical Reports Server (NTRS)

Birman, Kenneth; Cooper, Robert; Marzullo, Keith

1990-01-01

ISIS and META are two distributed systems projects at Cornell University. The ISIS project, has developed a new methodology, virtual synchrony, for writing robust distributed software. This approach is directly supported by the ISIS Toolkit, a programming system that is distributed to over 300 academic and industrial sites. Several interesting applications that exploit the strengths of ISIS, including an NFS-compatible replicated file system, are being developed. The META project, is about distributed control in a soft real time environment incorporating feedback. This domain encompasses examples as diverse as monitoring inventory and consumption on a factory floor and performing load-balancing on a distributed computing system. One of the first uses of META is for distributed application management: the tasks of configuring a distributed program, dynamically adapting to failures, and monitoring its performance. Recent progress and current plans are presented. This approach to distributed computing, a philosophy that is believed to significantly distinguish the work from that of others in the field, is explained.

Adaptive Problem Solving

DTIC Science & Technology

2017-03-01

AFRL-AFOSR-JP-TR-2017-0026 Adaptive Problem Solving Michael Barley THE UNIVERSITY OF AUCKLAND Final Report 03/01/2017 DISTRIBUTION A: Distribution...May 2015 to 26 Nov 2016 4. TITLE AND SUBTITLE Adaptive Problem Solving 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386-15-1-4069 5c.  PROGRAM ELEMENT...Report for AOARD Grant FA2386-15-1-4069 “ Adaptive Problem Solving” 25 February 2017 Name of Principal Investigators (PI): Michael W. Barley - e

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

Stout, Sherry; Hotchkiss, Eliza

Distributed generation can play a critical role in supporting climate adaptation goals. This infographic style poster will showcase the role of distributed generation in achieving a wide range of technical and policy goals and social services associated with climate adaptation.

Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

NASA Astrophysics Data System (ADS)

Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

Coordination of heterogeneous nonlinear multi-agent systems with prescribed behaviours

NASA Astrophysics Data System (ADS)

Tang, Yutao

2017-10-01

In this paper, we consider a coordination problem for a class of heterogeneous nonlinear multi-agent systems with a prescribed input-output behaviour which was represented by another input-driven system. In contrast to most existing multi-agent coordination results with an autonomous (virtual) leader, this formulation takes possible control inputs of the leader into consideration. First, the coordination was achieved by utilising a group of distributed observers based on conventional assumptions of model matching problem. Then, a fully distributed adaptive extension was proposed without using the input of this input-output behaviour. An example was given to verify their effectiveness.

Adaptation of an evidence-based intervention to promote colorectal cancer screening: a quasi-experimental study

PubMed Central

2014-01-01

Background To accelerate the translation of research findings into practice for underserved populations, we investigated the adaptation of an evidence-based intervention (EBI), designed to increase colorectal cancer (CRC) screening in one limited English-proficient (LEP) population (Chinese), for another LEP group (Vietnamese) with overlapping cultural and health beliefs. Methods Guided by Diffusion of Innovations Theory, we adapted the EBI to achieve greater reach. Core elements of the adapted intervention included: small media (a DVD and pamphlet) translated into Vietnamese from Chinese; medical assistants distributing the small media instead of a health educator; and presentations on CRC screening to the medical assistants. A quasi-experimental study examined CRC screening adherence among eligible Vietnamese patients at the intervention and control clinics, before and after the 24-month intervention. The proportion of the adherence was assessed using generalized linear mixed models that account for clustering under primary care providers and also within-patient correlation between baseline and follow up. Results Our study included two cross-sectional samples: 1,016 at baseline (604 in the intervention clinic and 412 in the control clinic) and 1,260 post-intervention (746 in the intervention and 514 in the control clinic), including appreciable overlaps between the two time points. Pre-post change in CRC screening over time, expressed as an odds ratio (OR) of CRC screening adherence by time, showed a marginally-significant greater increase in CRC screening adherence at the intervention clinic compared to the control clinic (the ratio of the two ORs = 1.42; 95% CI 0.95, 2.15). In the sample of patients who were non-adherent to CRC screening at baseline, compared to the control clinic, the intervention clinic had marginally-significant greater increase in FOBT (adjusted OR = 1.77; 95% CI 0.98, 3.18) and a statistically-significantly greater increase in CRC screening adherence (adjusted OR = 1.70; 95% CI 1.05, 2.75). Conclusions Theoretically guided adaptations of EBIs may accelerate the translation of research into practice. Adaptation has the potential to mitigate health disparities for hard-to-reach populations in a timely manner. PMID:24989083

Neural networks for continuous online learning and control.

PubMed

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

2006-11-01

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

Phenological plasticity will not help all species adapt to climate change.

PubMed

Duputié, Anne; Rutschmann, Alexis; Ronce, Ophélie; Chuine, Isabelle

2015-08-01

Concerns are rising about the capacity of species to adapt quickly enough to climate change. In long-lived organisms such as trees, genetic adaptation is slow, and how much phenotypic plasticity can help them cope with climate change remains largely unknown. Here, we assess whether, where and when phenological plasticity is and will be adaptive in three major European tree species. We use a process-based species distribution model, parameterized with extensive ecological data, and manipulate plasticity to suppress phenological variations due to interannual, geographical and trend climate variability, under current and projected climatic conditions. We show that phenological plasticity is not always adaptive and mostly affects fitness at the margins of the species' distribution and climatic niche. Under current climatic conditions, phenological plasticity constrains the northern range limit of oak and beech and the southern range limit of pine. Under future climatic conditions, phenological plasticity becomes strongly adaptive towards the trailing edges of beech and oak, but severely constrains the range and niche of pine. Our results call for caution when interpreting geographical variation in trait means as adaptive, and strongly point towards species distribution models explicitly taking phenotypic plasticity into account when forecasting species distribution under climate change scenarios. © 2015 John Wiley & Sons Ltd.

A Weibull distribution accrual failure detector for cloud computing

PubMed Central

Wu, Zhibo; Wu, Jin; Zhao, Yao; Wen, Dongxin

2017-01-01

Failure detectors are used to build high availability distributed systems as the fundamental component. To meet the requirement of a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. However, several implementations of accrual failure detectors do not adapt well to the cloud service environment. To solve this problem, a new accrual failure detector based on Weibull Distribution, called the Weibull Distribution Failure Detector, has been proposed specifically for cloud computing. It can adapt to the dynamic and unexpected network conditions in cloud computing. The performance of the Weibull Distribution Failure Detector is evaluated and compared based on public classical experiment data and cloud computing experiment data. The results show that the Weibull Distribution Failure Detector has better performance in terms of speed and accuracy in unstable scenarios, especially in cloud computing. PMID:28278229

Detection of Person Misfit in Computerized Adaptive Tests with Polytomous Items.

ERIC Educational Resources Information Center

van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R.

2002-01-01

Compared the nominal and empirical null distributions of the standardized log-likelihood statistic for polytomous items for paper-and-pencil (P&P) and computerized adaptive tests (CATs). Results show that the empirical distribution of the statistic differed from the assumed standard normal distribution for both P&P tests and CATs. Also…

A Neural Information Field Approach to Computational Cognition

DTIC Science & Technology

2016-11-18

We have extended our perceptual decision making model to account for the effects of context in this flexible DISTRIBUTION A. Approved for public...developed a new perceptual decision making model; demonstrated adaptive motor control in a large-scale cognitive simulation with spiking neurons (Spaun...TERMS EOARD, Computational Cognition, Mixed-initiative decision making 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF

Patterns of lake occupancy by fish indicate different adaptations to life in a harsh Arctic environment

USGS Publications Warehouse

Haynes, Trevor B.; Rosenberger, Amanda E.; Lindberg, Mark S.; Whitman, Matthew; Schmutz, Joel A.

2014-01-01

Based on these patterns, we propose an overall model of primary controls on the distribution of fish on the Arctic Coastal Plain of Alaska. Harsh conditions, including lake freezing, limit occupancy in winter through extinction events while lake occupancy in spring and summer is driven by directional migration (large-bodied species) and undirected dispersal (small-bodied species).

Deciphering the Adaptive Immune Response to Ovarian Cancer

DTIC Science & Technology

2015-12-01

REPORT: Final PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved...be construed as an official Department of the Army position, policy or decision unless so designated by other documentation. REPORT DOCUMENTATION...person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1994-01-01

The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

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.

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia

PubMed Central

Vojtkó, András; Farkas, Tünde; Szabó, Anna; Havadtői, Krisztina; Vojtkó, Anna E.; Tölgyesi, Csaba; Cseh, Viktória; Erdős, László; Maák, István Elek; Keppel, Gunnar

2017-01-01

Background and aims Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems. Methods We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses. Key Results Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes). Conclusions There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming. PMID:28025290

Large- and small-scale environmental factors drive distributions of cool-adapted plants in karstic microrefugia.

PubMed

Bátori, Zoltán; Vojtkó, András; Farkas, Tünde; Szabó, Anna; Havadtői, Krisztina; Vojtkó, Anna E; Tölgyesi, Csaba; Cseh, Viktória; Erdős, László; Maák, István Elek; Keppel, Gunnar

2017-01-01

Dolines are small- to large-sized bowl-shaped depressions of karst surfaces. They may constitute important microrefugia, as thermal inversion often maintains cooler conditions within them. This study aimed to identify the effects of large- (macroclimate) and small-scale (slope aspect and vegetation type) environmental factors on cool-adapted plants in karst dolines of East-Central Europe. We also evaluated the potential of these dolines to be microrefugia that mitigate the effects of climate change on cool-adapted plants in both forest and grassland ecosystems. We compared surveys of plant species composition that were made between 2007 and 2015 in 21 dolines distributed across four mountain ranges (sites) in Hungary and Romania. We examined the effects of environmental factors on the distribution and number of cool-adapted plants on three scales: (1) regional (all sites); (2) within sites and; (3) within dolines. Generalized linear models and non-parametric tests were used for the analyses. Macroclimate, vegetation type and aspect were all significant predictors of the diversity of cool-adapted plants. More cool-adapted plants were recorded in the coolest site, with only few found in the warmest site. At the warmest site, the distribution of cool-adapted plants was restricted to the deepest parts of dolines. Within sites of intermediate temperature and humidity, the effect of vegetation type and aspect on the diversity of cool-adapted plants was often significant, with more taxa being found in grasslands (versus forests) and on north-facing slopes (versus south-facing slopes). There is large variation in the number and spatial distribution of cool-adapted plants in karst dolines, which is related to large- and small-scale environmental factors. Both macro- and microrefugia are therefore likely to play important roles in facilitating the persistence of cool-adapted plants under global warming. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Optimal Bayesian Adaptive Design for Test-Item Calibration.

PubMed

van der Linden, Wim J; Ren, Hao

2015-06-01

An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

Adaptive random walks on the class of Web graphs

NASA Astrophysics Data System (ADS)

Tadić, B.

2001-09-01

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [B. Tadić, Physica A 293, 273 (2001)], and are characterized by a pair of power-law distributions of out- and in-degree for each value of the parameter β, which measures the degree of rewiring in the graph. The walker adapts its move strategy according to locally available information both on out-degree of the visited node and in-degree of target node. A standard random walk, on the other hand, uses the out-degree only. We compute the distribution of connected subgraphs visited by an ensemble of walkers, the average access time and survival probability of the walks. We discuss these properties of the walk dynamics relative to the changes in the global graph structure when the control parameter β is varied. For β≥ 3, corresponding to the world-wide Web, the access time of the walk to a given level of hierarchy on the graph is much shorter compared to the standard random walk on the same graph. By reducing the amount of rewiring towards rigidity limit β↦βc≲ 0.1, corresponding to the range of naturally occurring biochemical networks, the survival probability of adaptive and standard random walk become increasingly similar. The adaptive random walk can be used as an efficient message-passing algorithm on this class of graphs for large degree of rewiring.

Controlling the Laser Guide Star power density distribution at Sodium layer by combining Pre-correction and Beam-shaping

NASA Astrophysics Data System (ADS)

Huang, Jian; Wei, Kai; Jin, Kai; Li, Min; Zhang, YuDong

2018-06-01

The Sodium laser guide star (LGS) plays a key role in modern astronomical Adaptive Optics Systems (AOSs). The spot size and photon return of the Sodium LGS depend strongly on the laser power density distribution at the Sodium layer and thus affect the performance of the AOS. The power density distribution is degraded by turbulence in the uplink path, launch system aberrations, the beam quality of the laser, and so forth. Even without any aberrations, the TE00 Gaussian type is still not the optimal power density distribution to obtain the best balance between the measurement error and temporal error. To optimize and control the LGS power density distribution at the Sodium layer to an expected distribution type, a method that combines pre-correction and beam-shaping is proposed. A typical result shows that under strong turbulence (Fried parameter (r0) of 5 cm) and for a quasi-continuous wave Sodium laser (power (P) of 15 W), in the best case, our method can effectively optimize the distribution from the Gaussian type to the "top-hat" type and enhance the photon return flux of the Sodium LGS; at the same time, the total error of the AOS is decreased by 36% with our technique for a high power laser and poor seeing.

Measuring static seated pressure distributions and risk for skin pressure ulceration in ice sledge hockey players.

PubMed

Darrah, Shaun D; Dicianno, Brad E; Berthold, Justin; McCoy, Andrew; Haas, Matthew; Cooper, Rory A

2016-01-01

To determine whether sledge hockey players with physical disability have higher average seated pressures compared to non-disabled controls. Fifteen age-matched controls without physical disability and 15 experimental participants with physical disability were studied using a pressure mapping device to determine risk for skin pressure ulceration and the impact of cushioning and knee angle positioning on seated pressure distributions. Regardless of participant group, cushioning, or knee angle, average seated pressures exceeded clinically acceptable seated pressures. Controls had significantly higher average seated pressures than the disability group when knees were flexed, both with the cushion (p = 0.013) and without (p = 0.015). Knee extension showed significantly lower average pressures in controls, both with the cushion (p < 0.001) and without (p < 0.001). Placement of the cushion resulted in significantly lower average pressure in controls when knees were extended (p = 0.024) but not when flexed (p = 0.248). Placement of the cushion resulted in no difference in pressure (p = 0.443) in the disability group. Pressures recorded indicate high risk for skin ulceration. Cushioning was effective only in the control group with knees extended. That knee extension significantly lowered average seated pressures is important, as many sledge hockey players utilize positioning with larger knee flexion angles. Implications for Rehabilitation Ice sledge hockey is a fast growing adaptive sport. Adaptive sports have been associated with several positive improvements in overall health and quality of life, though may be putting players at risk for skin ulceration. Measured static seated pressure in sledges greatly exceeds current clinically accepted clinical guidelines. With modern improvements in wheelchair pressure relief/cushioning there are potential methods for improvement of elevated seated pressure in ice hockey sledges.

Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

NASA Technical Reports Server (NTRS)

Trujillo, Anna; Gregory, Irene

2013-01-01

Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.

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.

KSC-98pc151

NASA Image and Video Library

1998-01-14

The Photovoltaic Module 1 Integrated Equipment Assembly (IEA) is moved past a Pressurized Mating Adapter in Kennedy Space Center’s Space Station Processing Facility (SSPF) toward the workstand where it will be processed for flight on STS-97, scheduled for launch in April 1999. The IEA is one of four integral units designed to generate, distribute, and store power for the International Space Station. It will carry solar arrays, power storage batteries, power control units, and a thermal control system. The 16-foot-long, 16,850-pound unit is now undergoing preflight preparations in the SSPF

An overview of controls research on the NASA Langley Research Center grid

NASA Technical Reports Server (NTRS)

Montgomery, Raymond C.

1987-01-01

The NASA Langley Research Center has assembled a flexible grid on which control systems research can be accomplished on a two-dimensional structure that has many physically distributed sensors and actuators. The grid is a rectangular planar structure that is suspended by two cables attached to one edge so that out of plane vibrations are normal to gravity. There are six torque wheel actuators mounted to it so that torque is produced in the grid plane. Also, there are six rate gyros mounted to sense angular motion in the grid plane and eight accelerometers that measure linear acceleration normal to the grid plane. All components can be relocated to meet specific control system test requirements. Digital, analog, and hybrid control systems capability is provided in the apparatus. To date, research on this grid has been conducted in the areas of system and parameter identification, model estimation, distributed modal control, hierarchical adaptive control, and advanced redundancy management algorithms. The presentation overviews each technique and presents the most significant results generated for each area.

Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations

PubMed Central

Good, Benjamin H.; Rouzine, Igor M.; Balick, Daniel J.; Hallatschek, Oskar; Desai, Michael M.

2012-01-01

When large asexual populations adapt, competition between simultaneously segregating mutations slows the rate of adaptation and restricts the set of mutations that eventually fix. This phenomenon of interference arises from competition between mutations of different strengths as well as competition between mutations that arise on different fitness backgrounds. Previous work has explored each of these effects in isolation, but the way they combine to influence the dynamics of adaptation remains largely unknown. Here, we describe a theoretical model to treat both aspects of interference in large populations. We calculate the rate of adaptation and the distribution of fixed mutational effects accumulated by the population. We focus particular attention on the case when the effects of beneficial mutations are exponentially distributed, as well as on a more general class of exponential-like distributions. In both cases, we show that the rate of adaptation and the influence of genetic background on the fixation of new mutants is equivalent to an effective model with a single selection coefficient and rescaled mutation rate, and we explicitly calculate these effective parameters. We find that the effective selection coefficient exactly coincides with the most common fixed mutational effect. This equivalence leads to an intuitive picture of the relative importance of different types of interference effects, which can shift dramatically as a function of the population size, mutation rate, and the underlying distribution of fitness effects. PMID:22371564

Distributed computing environments for future space control systems

NASA Technical Reports Server (NTRS)

Viallefont, Pierre

1993-01-01

The aim of this paper is to present the results of a CNES research project on distributed computing systems. The purpose of this research was to study the impact of the use of new computer technologies in the design and development of future space applications. The first part of this study was a state-of-the-art review of distributed computing systems. One of the interesting ideas arising from this review is the concept of a 'virtual computer' allowing the distributed hardware architecture to be hidden from a software application. The 'virtual computer' can improve system performance by adapting the best architecture (addition of computers) to the software application without having to modify its source code. This concept can also decrease the cost and obsolescence of the hardware architecture. In order to verify the feasibility of the 'virtual computer' concept, a prototype representative of a distributed space application is being developed independently of the hardware architecture.

Structural optimization of 3D-printed synthetic spider webs for high strength

NASA Astrophysics Data System (ADS)

Qin, Zhao; Compton, Brett G.; Lewis, Jennifer A.; Buehler, Markus J.

2015-05-01

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

Structural optimization of 3D-printed synthetic spider webs for high strength.

PubMed

Qin, Zhao; Compton, Brett G; Lewis, Jennifer A; Buehler, Markus J

2015-05-15

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations.

Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables

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

DallAnese, Emiliano; Baker, Kyri; Summers, Tyler

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrarymore » distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.« less

A Systems Approach to Manage Drinking Water Quality ...

EPA Pesticide Factsheets

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate the water supply vulnerability and examine technological options in adaptation. Total organic carbon (TOC) in surface water can vary significantly due to changes or a combination of changes in watershed land use, climate variability, and extreme meteorological events (e.g., hurricanes). On the other hand, water demand is known to vary temporarily and spatially leading to changes in water ages and hence DBP formation potential. Typically a drinking water facility is designed to operate within a projected range of influent water quality and water demand. When the variations exceed the design range, water supply becomes vulnerable in the compliance to Safe Drinking Water Act (SDWA) Stage-II disinfection by-product (DBP) rules. This paper describes a framework of systems-level modeling, monitoring and control in adaptive planning and system operation. The framework, built upon the integration of model projections, adaptive monitoring and systems control, has three primary functions. Its advantages and limitations will be discussed with the application examples in Cincinnati (Ohio, USA) and Las Vegas (Nevada, USA). At a conceptual level, an integrated land use and hydrological model

Adaptive graph-based multiple testing procedures

PubMed Central

Klinglmueller, Florian; Posch, Martin; Koenig, Franz

2016-01-01

Multiple testing procedures defined by directed, weighted graphs have recently been proposed as an intuitive visual tool for constructing multiple testing strategies that reflect the often complex contextual relations between hypotheses in clinical trials. Many well-known sequentially rejective tests, such as (parallel) gatekeeping tests or hierarchical testing procedures are special cases of the graph based tests. We generalize these graph-based multiple testing procedures to adaptive trial designs with an interim analysis. These designs permit mid-trial design modifications based on unblinded interim data as well as external information, while providing strong family wise error rate control. To maintain the familywise error rate, it is not required to prespecify the adaption rule in detail. Because the adaptive test does not require knowledge of the multivariate distribution of test statistics, it is applicable in a wide range of scenarios including trials with multiple treatment comparisons, endpoints or subgroups, or combinations thereof. Examples of adaptations are dropping of treatment arms, selection of subpopulations, and sample size reassessment. If, in the interim analysis, it is decided to continue the trial as planned, the adaptive test reduces to the originally planned multiple testing procedure. Only if adaptations are actually implemented, an adjusted test needs to be applied. The procedure is illustrated with a case study and its operating characteristics are investigated by simulations. PMID:25319733

Adaptation to stimulus statistics in the perception and neural representation of auditory space.

PubMed

Dahmen, Johannes C; Keating, Peter; Nodal, Fernando R; Schulz, Andreas L; King, Andrew J

2010-06-24

Sensory systems are known to adapt their coding strategies to the statistics of their environment, but little is still known about the perceptual implications of such adjustments. We investigated how auditory spatial processing adapts to stimulus statistics by presenting human listeners and anesthetized ferrets with noise sequences in which interaural level differences (ILD) rapidly fluctuated according to a Gaussian distribution. The mean of the distribution biased the perceived laterality of a subsequent stimulus, whereas the distribution's variance changed the listeners' spatial sensitivity. The responses of neurons in the inferior colliculus changed in line with these perceptual phenomena. Their ILD preference adjusted to match the stimulus distribution mean, resulting in large shifts in rate-ILD functions, while their gain adapted to the stimulus variance, producing pronounced changes in neural sensitivity. Our findings suggest that processing of auditory space is geared toward emphasizing relative spatial differences rather than the accurate representation of absolute position.

Virtual-system-coupled adaptive umbrella sampling to compute free-energy landscape for flexible molecular docking.

PubMed

Higo, Junichi; Dasgupta, Bhaskar; Mashimo, Tadaaki; Kasahara, Kota; Fukunishi, Yoshifumi; Nakamura, Haruki

2015-07-30

A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35 ) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc.

Flexible structure control laboratory development and technology demonstration

NASA Technical Reports Server (NTRS)

Vivian, H. C.; Blaire, P. E.; Eldred, D. B.; Fleischer, G. E.; Ih, C.-H. C.; Nerheim, N. M.; Scheid, R. E.; Wen, J. T.

1987-01-01

An experimental structure is described which was constructed to demonstrate and validate recent emerging technologies in the active control and identification of large flexible space structures. The configuration consists of a large, 20 foot diameter antenna-like flexible structure in the horizontal plane with a gimballed central hub, a flexible feed-boom assembly hanging from the hub, and 12 flexible ribs radiating outward. Fourteen electrodynamic force actuators mounted to the hub and to the individual ribs provide the means to excite the structure and exert control forces. Thirty permanently mounted sensors, including optical encoders and analog induction devices provide measurements of structural response at widely distributed points. An experimental remote optical sensor provides sixteen additional sensing channels. A computer samples the sensors, computes the control updates and sends commands to the actuators in real time, while simultaneously displaying selected outputs on a graphics terminal and saving them in memory. Several control experiments were conducted thus far and are documented. These include implementation of distributed parameter system control, model reference adaptive control, and static shape control. These experiments have demonstrated the successful implementation of state-of-the-art control approaches using actual hardware.

Learning multivariate distributions by competitive assembly of marginals.

PubMed

Sánchez-Vega, Francisco; Younes, Laurent; Geman, Donald

2013-02-01

We present a new framework for learning high-dimensional multivariate probability distributions from estimated marginals. The approach is motivated by compositional models and Bayesian networks, and designed to adapt to small sample sizes. We start with a large, overlapping set of elementary statistical building blocks, or "primitives," which are low-dimensional marginal distributions learned from data. Each variable may appear in many primitives. Subsets of primitives are combined in a Lego-like fashion to construct a probabilistic graphical model; only a small fraction of the primitives will participate in any valid construction. Since primitives can be precomputed, parameter estimation and structure search are separated. Model complexity is controlled by strong biases; we adapt the primitives to the amount of training data and impose rules which restrict the merging of them into allowable compositions. The likelihood of the data decomposes into a sum of local gains, one for each primitive in the final structure. We focus on a specific subclass of networks which are binary forests. Structure optimization corresponds to an integer linear program and the maximizing composition can be computed for reasonably large numbers of variables. Performance is evaluated using both synthetic data and real datasets from natural language processing and computational biology.

Adaptive Flight Control for Aircraft Safety Enhancements

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Gregory, Irene M.; Joshi, Suresh M.

2008-01-01

This poster presents the current adaptive control research being conducted at NASA ARC and LaRC in support of the Integrated Resilient Aircraft Control (IRAC) project. The technique "Approximate Stability Margin Analysis of Hybrid Direct-Indirect Adaptive Control" has been developed at NASA ARC to address the needs for stability margin metrics for adaptive control that potentially enables future V&V of adaptive systems. The technique "Direct Adaptive Control With Unknown Actuator Failures" is developed at NASA LaRC to deal with unknown actuator failures. The technique "Adaptive Control with Adaptive Pilot Element" is being researched at NASA LaRC to investigate the effects of pilot interactions with adaptive flight control that can have implications of stability and performance.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2018-01-01

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Co-Adaptive Aiding and Automation Enhance Operator Performance

DTIC Science & Technology

2013-03-01

activation system. There is a close relation between physiologically activated adaptive aiding and brain- computer interfaces ( BCI ). BCI here refers...classification of EEG signals (Farwell & Donchin, 1988). Physiologically activated adaptive aiding is, in a sense, a special case of BCI wherein the...as passive BCI , e.g. Zander, Kothe, Jatzev, & 3 Distribution A: Approved for public release; distribution unlimited. 88 ABW Cleared 05/13/2013

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

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.

Within-twig leaf distribution patterns differ among plant life-forms in a subtropical Chinese forest.

PubMed

Meng, Fengqun; Cao, Rui; Yang, Dongmei; Niklas, Karl J; Sun, Shucun

2013-07-01

In theory, plants can alter the distribution of leaves along the lengths of their twigs (i.e., within-twig leaf distribution patterns) to optimize light interception in the context of the architectures of their leaves, branches and canopies. We hypothesized that (i) among canopy tree species sharing similar light environments, deciduous trees will have more evenly spaced within-twig leaf distribution patterns compared with evergreen trees (because deciduous species tend to higher metabolic demands than evergreen species and hence require more light), and that (ii) shade-adapted evergreen species will have more evenly spaced patterns compared with sun-adapted evergreen ones (because shade-adapted species are generally light-limited). We tested these hypotheses by measuring morphological traits (i.e., internode length, leaf area, lamina mass per area, LMA; and leaf and twig inclination angles to the horizontal) and physiological traits (i.e., light-saturated net photosynthetic rates, Amax; light saturation points, LSP; and light compensation points, LCP), and calculated the 'evenness' of within-twig leaf distribution patterns as the coefficient of variation (CV; the higher the CV, the less evenly spaced leaves) of within-twig internode length for 9 deciduous canopy tree species, 15 evergreen canopy tree species, 8 shade-adapted evergreen shrub species and 12 sun-adapted evergreen shrub species in a subtropical broad-leaved rainforest in eastern China. Coefficient of variation was positively correlated with large LMA and large leaf and twig inclination angles, which collectively specify a typical trait combination adaptive to low light interception, as indicated by both ordinary regression and phylogenetic generalized least squares analyses. These relationships were also valid within the evergreen tree species group (which had the largest sample size). Consistent with our hypothesis, in the canopy layer, deciduous species (which were characterized by high LCP, LSP and Amax) had more even leaf distribution patterns than evergreen species (which had low LCP, LSP and Amax); shade-adapted evergreen species had more even leaf distribution patterns than sun-adapted evergreen species. We propose that the leaf distribution pattern (i.e., 'evenness' CV, which is an easily measured functional trait) can be used to distinguish among life-forms in communities similar to the one examined in this study.

Reliable Adaptive Video Streaming Driven by Perceptual Semantics for Situational Awareness

PubMed Central

Pimentel-Niño, M. A.; Saxena, Paresh; Vazquez-Castro, M. A.

2015-01-01

A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account feedback on network congestion (time) and erasures (space) to best distribute available (scarce) bandwidth. Systematic random linear network coding (SRNC) adds reliability while preserving perceptual semantics. Objective metrics of the perceptual features in QoE show homogeneous high performance when using the proposed scheme. Finally, the proposed scheme is in line with content-aware trends, by complying with information-centric-networking philosophy and architecture. PMID:26247057

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Issac; Kitsios, Ioannis; Cao, Chengyu; Gregory, Irene M.; Valavani, Lena

2010-01-01

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

Local host specialization, host-switching, and dispersal shape the regional distributions of avian haemosporidian parasites.

PubMed

Ellis, Vincenzo A; Collins, Michael D; Medeiros, Matthew C I; Sari, Eloisa H R; Coffey, Elyse D; Dickerson, Rebecca C; Lugarini, Camile; Stratford, Jeffrey A; Henry, Donata R; Merrill, Loren; Matthews, Alix E; Hanson, Alison A; Roberts, Jackson R; Joyce, Michael; Kunkel, Melanie R; Ricklefs, Robert E

2015-09-08

The drivers of regional parasite distributions are poorly understood, especially in comparison with those of free-living species. For vector-transmitted parasites, in particular, distributions might be influenced by host-switching and by parasite dispersal with primary hosts and vectors. We surveyed haemosporidian blood parasites (Plasmodium and Haemoproteus) of small land birds in eastern North America to characterize a regional parasite community. Distributions of parasite populations generally reflected distributions of their hosts across the region. However, when the interdependence between hosts and parasites was controlled statistically, local host assemblages were related to regional climatic gradients, but parasite assemblages were not. Moreover, because parasite assemblage similarity does not decrease with distance when controlling for host assemblages and climate, parasites evidently disperse readily within the distributions of their hosts. The degree of specialization on hosts varied in some parasite lineages over short periods and small geographic distances independently of the diversity of available hosts and potentially competing parasite lineages. Nonrandom spatial turnover was apparent in parasite lineages infecting one host species that was well-sampled within a single year across its range, plausibly reflecting localized adaptations of hosts and parasites. Overall, populations of avian hosts generally determine the geographic distributions of haemosporidian parasites. However, parasites are not dispersal-limited within their host distributions, and they may switch hosts readily.

Distribution of Intelligence in Airborne Air-Defense Mission Systems

DTIC Science & Technology

2001-03-01

their ,,creator" has given them a structure - not only a program - allowing them to organize themselves, to learn and to adapt themselves to changing...self- organization capability. They are modelled on the structures of the unconscious mind. "• By contrast, fuzzy logic/fuzzy control has developed an...of these techniques as indicated in Fig. 3 is of particular importance for achieving unprecedented levels of self- organization capability and

Command and Control of Joint Air Operations through Mission Command

DTIC Science & Technology

2016-06-01

and outlines the C2 architecture systems, processes, and philosophy of com- mand required to enable mission command effectively. Mission Command...General Dempsey highlights the fact that “trust is the moral sinew that binds the distributed Joint Force 2020 together” and observes that “unless...con- fident about how their subordinates will make decisions and adapt to the dynamic battlespace environment. Processes, Systems, and Philosophy of

On mobile wireless ad hoc IP video transports

NASA Astrophysics Data System (ADS)

Kazantzidis, Matheos

2006-05-01

Multimedia transports in wireless, ad-hoc, multi-hop or mobile networks must be capable of obtaining information about the network and adaptively tune sending and encoding parameters to the network response. Obtaining meaningful metrics to guide a stable congestion control mechanism in the transport (i.e. passive, simple, end-to-end and network technology independent) is a complex problem. Equally difficult is obtaining a reliable QoS metrics that agrees with user perception in a client/server or distributed environment. Existing metrics, objective or subjective, are commonly used after or before to test or report on a transmission and require access to both original and transmitted frames. In this paper, we propose that an efficient and successful video delivery and the optimization of overall network QoS requires innovation in a) a direct measurement of available and bottleneck capacity for its congestion control and b) a meaningful subjective QoS metric that is dynamically reported to video sender. Once these are in place, a binomial -stable, fair and TCP friendly- algorithm can be used to determine the sending rate and other packet video parameters. An adaptive mpeg codec can then continually test and fit its parameters and temporal-spatial data-error control balance using the perceived QoS dynamic feedback. We suggest a new measurement based on a packet dispersion technique that is independent of underlying network mechanisms. We then present a binomial control based on direct measurements. We implement a QoS metric that is known to agree with user perception (MPQM) in a client/server, distributed environment by using predetermined table lookups and characterization of video content.

Effects of disease severity and medication state on postural control asymmetry during challenging postural tasks in individuals with Parkinson's disease.

PubMed

Barbieri, Fabio A; Polastri, Paula F; Baptista, André M; Lirani-Silva, Ellen; Simieli, Lucas; Orcioli-Silva, Diego; Beretta, Victor S; Gobbi, Lilian T B

2016-04-01

The aim of this study was to investigate the effects of disease severity and medication state on postural control asymmetry during challenging tasks in individuals with Parkinson's disease (PD). Nineteen people with PD and 11 neurologically healthy individuals performed three standing task conditions: bipedal standing, tandem and unipedal adapted standing; the individuals with PD performed the tasks in ON and OFF medication state. The participants with PD were distributed into 2 groups according to disease severity: unilateral group (n=8) and bilateral group (n=11). The two PD groups performed the evaluations both under and without the medication. Two force plates were used to analyze the posture. The symmetric index was calculated for various of center of pressure. ANOVA one-way (groups) and two-way (PD groups×medication), with repeated measures for medication, were calculated. For main effects of group, the bilateral group was more asymmetric than CG. For main effects of medication, only unipedal adapted standing presented effects of PD medication. There was PD groups×medication interaction. Under the effects of medication, the unilateral group presented lower asymmetry of RMS in anterior-posterior direction and area than the bilateral group in unipedal adapted standing. In addition, the unilateral group presented lower asymmetry of mean velocity, RMS in anterior-posterior direction and area in unipedal standing and area in tandem adapted standing after a medication dose. Postural control asymmetry during challenging postural tasks was dependent on disease severity and medication state in people with PD. The bilateral group presented higher postural control asymmetry than the control and unilateral groups in challenging postural tasks. Finally, the medication dose was able to reduce postural control asymmetry in the unilateral group during challenging postural tasks. Copyright © 2015 Elsevier B.V. All rights reserved.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System.

PubMed

Liu, Ying-Pei; Liang, Hai-Ping; Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System

PubMed Central

Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane. PMID:26098556

Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

NASA Astrophysics Data System (ADS)

Sardinha-Lourenço, A.; Andrade-Campos, A.; Antunes, A.; Oliveira, M. S.

2018-03-01

Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24-48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

[A comparison of maternal psychosocial adaptation among pregnant women with different gravidity].

PubMed

Lin, Chun-Ting; Chou, Fan-Hao

2008-12-01

The purpose of this study was to examine women's psychosocial adaptation during different trimesters of pregnancy and to compare maternal psychosocial adaptation between primigravida and multigravida. A cross-sectional and comparative research design was conducted. A convenience sample consisting of 717 pregnant women who made a prenatal clinical visit in southern Taiwan were recruited for this study. The sample included 369 primigravida and 348 multigravida. A Demographic Inventory and the Chinese version of the Prenatal Self-Evaluation Questionnaire (PSEQ) were used to collect data. Results found that (1) the subscale "relationship with husband" for multigravida showed statistically significant differences between the three trimesters, with scores for the third trimester higher than those for the first. Also, multigravida had poorer adaptation on "relationship with husband" in the third trimester than in the first; (2) Analysis of covariance was used to adjust for age, marital status and planned pregnancy, as the distribution of such variables was significantly different between primigravida and multigravida. Results showed significant differences between the two sample groups in terms of PSEQ total scores and scores for "concern for well-being of self and baby," "preparation for labor," and "fear of helplessness, and loss of control in labor." This indicates that primigravida had poorer maternal psychosocial adaptation than multigravida and worried more about "concern for well-being of self and baby," "preparation for labor," and "fear of helplessness, and loss of control in labor." The findings of this study provide evidence-based data to help nursing professionals provide more suitable nursing care to pregnant women. Nurses should assess pregnant women's psychosocial adaptation during their prenatal visiting and then assist them to better understand the process of childbirth and enhance their level of control during labor. In addition, nurses should appraise women's relationships with their husbands during the third trimester and supply appropriate nursing care to pregnant women for a more pleasant pregnancy and labor experience.

Gesteme-free context-aware adaptation of robot behavior in human-robot cooperation.

PubMed

Nessi, Federico; Beretta, Elisa; Gatti, Cecilia; Ferrigno, Giancarlo; De Momi, Elena

2016-11-01

Cooperative robotics is receiving greater acceptance because the typical advantages provided by manipulators are combined with an intuitive usage. In particular, hands-on robotics may benefit from the adaptation of the assistant behavior with respect to the activity currently performed by the user. A fast and reliable classification of human activities is required, as well as strategies to smoothly modify the control of the manipulator. In this scenario, gesteme-based motion classification is inadequate because it needs the observation of a wide signal percentage and the definition of a rich vocabulary. In this work, a system able to recognize the user's current activity without a vocabulary of gestemes, and to accordingly adapt the manipulator's dynamic behavior is presented. An underlying stochastic model fits variations in the user's guidance forces and the resulting trajectories of the manipulator's end-effector with a set of Gaussian distribution. The high-level switching between these distributions is captured with hidden Markov models. The dynamic of the KUKA light-weight robot, a torque-controlled manipulator, is modified with respect to the classified activity using sigmoidal-shaped functions. The presented system is validated over a pool of 12 näive users in a scenario that addresses surgical targeting tasks on soft tissue. The robot's assistance is adapted in order to obtain a stiff behavior during activities that require critical accuracy constraint, and higher compliance during wide movements. Both the ability to provide the correct classification at each moment (sample accuracy) and the capability of correctly identify the correct sequence of activity (sequence accuracy) were evaluated. The proposed classifier is fast and accurate in all the experiments conducted (80% sample accuracy after the observation of ∼450ms of signal). Moreover, the ability of recognize the correct sequence of activities, without unwanted transitions is guaranteed (sequence accuracy ∼90% when computed far away from user desired transitions). Finally, the proposed activity-based adaptation of the robot's dynamic does not lead to a not smooth behavior (high smoothness, i.e. normalized jerk score <0.01). The provided system is able to dynamic assist the operator during cooperation in the presented scenario. Copyright © 2016 Elsevier B.V. All rights reserved.

Adaptive control applied to Space Station attitude control system

NASA Technical Reports Server (NTRS)

Lam, Quang M.; Chipman, Richard; Hu, Tsay-Hsin G.; Holmes, Eric B.; Sunkel, John

1992-01-01

This paper presents an adaptive control approach to enhance the performance of current attitude control system used by the Space Station Freedom. The proposed control law was developed based on the direct adaptive control or model reference adaptive control scheme. Performance comparisons, subject to inertia variation, of the adaptive controller and the fixed-gain linear quadratic regulator currently implemented for the Space Station are conducted. Both the fixed-gain and the adaptive gain controllers are able to maintain the Station stability for inertia variations of up to 35 percent. However, when a 50 percent inertia variation is applied to the Station, only the adaptive controller is able to maintain the Station attitude.

Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Boskovic, Jovan D.

2008-01-01

This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Space Flight Operations Center local area network

NASA Technical Reports Server (NTRS)

Goodman, Ross V.

1988-01-01

The existing Mission Control and Computer Center at JPL will be replaced by the Space Flight Operations Center (SFOC). One part of the SFOC is the LAN-based distribution system. The purpose of the LAN is to distribute the processed data among the various elements of the SFOC. The SFOC LAN will provide a robust subsystem that will support the Magellan launch configuration and future project adaptation. Its capabilities include (1) a proven cable medium as the backbone for the entire network; (2) hardware components that are reliable, varied, and follow OSI standards; (3) accurate and detailed documentation for fault isolation and future expansion; and (4) proven monitoring and maintenance tools.

Ion-optical studies for a range adaptation method in ion beam therapy using a static wedge degrader combined with magnetic beam deflection.

PubMed

Chaudhri, Naved; Saito, Nami; Bert, Christoph; Franczak, Bernhard; Steidl, Peter; Durante, Marco; Rietzel, Eike; Schardt, Dieter

2010-06-21

Fast radiological range adaptation of the ion beam is essential when target motion is mitigated by beam tracking using scanned ion beams for dose delivery. Electromagnetically controlled deflection of a well-focused ion beam on a small static wedge degrader positioned between two dipole magnets, inside the beam delivery system, has been considered as a fast range adaptation method. The principle of the range adaptation method was tested in experiments and Monte Carlo simulations for the therapy beam line at the GSI Helmholtz Centre for Heavy Ions Research. Based on the simulations, ion optical settings of beam deflection and realignment of the adapted beam were experimentally applied to the beam line, and additional tuning was manually performed. Different degrader shapes were employed for the energy adaptation. Measured and simulated beam profiles, i.e. lateral distribution and range in water at isocentre, were analysed and compared with the therapy beam values for beam scanning. Deflected beam positions of up to +/-28 mm on degrader were performed which resulted in a range adaptation of up to +/-15 mm water equivalence (WE). The maximum deviation between the measured adapted range from the nominal range adaptation was below 0.4 mm WE. In experiments, the width of the adapted beam at the isocentre was adjustable between 5 and 11 mm full width at half maximum. The results demonstrate the feasibility/proof of the proposed range adaptation method for beam tracking from the beam quality point of view.

SAGE - MULTIDIMENSIONAL SELF-ADAPTIVE GRID CODE

NASA Technical Reports Server (NTRS)

Davies, C. B.

1994-01-01

SAGE, Self Adaptive Grid codE, is a flexible tool for adapting and restructuring both 2D and 3D grids. Solution-adaptive grid methods are useful tools for efficient and accurate flow predictions. In supersonic and hypersonic flows, strong gradient regions such as shocks, contact discontinuities, shear layers, etc., require careful distribution of grid points to minimize grid error and produce accurate flow-field predictions. SAGE helps the user obtain more accurate solutions by intelligently redistributing (i.e. adapting) the original grid points based on an initial or interim flow-field solution. The user then computes a new solution using the adapted grid as input to the flow solver. The adaptive-grid methodology poses the problem in an algebraic, unidirectional manner for multi-dimensional adaptations. The procedure is analogous to applying tension and torsion spring forces proportional to the local flow gradient at every grid point and finding the equilibrium position of the resulting system of grid points. The multi-dimensional problem of grid adaption is split into a series of one-dimensional problems along the computational coordinate lines. The reduced one dimensional problem then requires a tridiagonal solver to find the location of grid points along a coordinate line. Multi-directional adaption is achieved by the sequential application of the method in each coordinate direction. The tension forces direct the redistribution of points to the strong gradient region. To maintain smoothness and a measure of orthogonality of grid lines, torsional forces are introduced that relate information between the family of lines adjacent to one another. The smoothness and orthogonality constraints are direction-dependent, since they relate only the coordinate lines that are being adapted to the neighboring lines that have already been adapted. Therefore the solutions are non-unique and depend on the order and direction of adaption. Non-uniqueness of the adapted grid is acceptable since it makes possible an overall and local error reduction through grid redistribution. SAGE includes the ability to modify the adaption techniques in boundary regions, which substantially improves the flexibility of the adaptive scheme. The vectorial approach used in the analysis also provides flexibility. The user has complete choice of adaption direction and order of sequential adaptions without concern for the computational data structure. Multiple passes are available with no restraint on stepping directions; for each adaptive pass the user can choose a completely new set of adaptive parameters. This facility, combined with the capability of edge boundary control, enables the code to individually adapt multi-dimensional multiple grids. Zonal grids can be adapted while maintaining continuity along the common boundaries. For patched grids, the multiple-pass capability enables complete adaption. SAGE is written in FORTRAN 77 and is intended to be machine independent; however, it requires a FORTRAN compiler which supports NAMELIST input. It has been successfully implemented on Sun series computers, SGI IRIS's, DEC MicroVAX computers, HP series computers, the Cray YMP, and IBM PC compatibles. Source code is provided, but no sample input and output files are provided. The code reads three datafiles: one that contains the initial grid coordinates (x,y,z), one that contains corresponding flow-field variables, and one that contains the user control parameters. It is assumed that the first two datasets are formatted as defined in the plotting software package PLOT3D. Several machine versions of PLOT3D are available from COSMIC. The amount of main memory is dependent on the size of the matrix. The standard distribution medium for SAGE is a 5.25 inch 360K MS-DOS format diskette. It is also available on a .25 inch streaming magnetic tape cartridge in UNIX tar format or on a 9-track 1600 BPI ASCII CARD IMAGE format magnetic tape. SAGE was developed in 1989, first released as a 2D version in 1991 and updated to 3D in 1993.

Adaptive protection algorithm and system

DOEpatents

Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

2009-04-28

An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

Optimization of the central automatic control of a small Dutch sewer system

NASA Astrophysics Data System (ADS)

Kolechkina, A. G.; Hoes, O. A. C.

2012-04-01

A sewer control system was developed in the context of a subsidized project aiming at improvement of surface water quality by control of sewer systems and surface water systems. The project was coordinated by the local water board, "Waterschap Hollandse Delta". Other participants were Delft University of Technology, Deltares and the municipalities Strijen, Cromstrijen, Westmaas, Oud Beijerland and Piershil. As part of the project there were two pilot implementations where a central automatic controller was coupled to the existing SCADA system. For these two pilots the system is now operational. A Dutch urban area in the western part of the Netherlands is usually part of a polder, which is effectively an artificially drained catchment. The urban area itself is split into small subcatchments that manage runoff in different ways. In all cases a large fraction goes into the natural hydrological cycle, but, depending on the design of the local sewer system, a larger or smaller part finds its way into the sewer system. Proper control of this flow is necessary to control surface water quality and to avoid health risks from flow from the sewer into the streets. At each time step the controller switches pumps to distribute the remaining water in the system at the end of the time step over the different subcatchments. The distribution is created based on expert judgment of the relative vulnerability and subcatchment sewer system water quality. It is implemented in terms curves of total system stored volume versus subcatchment stored volume. We describe the process of the adaptation of a controller to two different sewer systems and the understanding of the artificial part of the catchment we gained during this process. In the process of adaptation the type of sewer system (combined foul water and storm water transport or separate foul water and storm water transport) played a major role.

Development of Control Models and a Robust Multivariable Controller for Surface Shape Control

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

Winters, Scott Eric

2003-06-18

Surface shape control techniques are applied to many diverse disciplines, such as adaptive optics, noise control, aircraft flutter control and satellites, with an objective to achieve a desirable shape for an elastic body by the application of distributed control forces. Achieving the desirable shape is influenced by many factors, such as, actuator locations, sensor locations, surface precision and controller performance. Building prototypes to complete design optimizations or controller development can be costly or impractical. This shortfall, puts significant value in developing accurate modeling and control simulation approaches. This thesis focuses on the field of adaptive optics, although these developments havemore » the potential for application in many other fields. A static finite element model is developed and validated using a large aperture interferometer system. This model is then integrated into a control model using a linear least squares algorithm and Shack-Hartmann sensor. The model is successfully exercised showing functionality for various wavefront aberrations. Utilizing a verified model shows significant value in simulating static surface shape control problems with quantifiable uncertainties. A new dynamic model for a seven actuator deformable mirror is presented and its accuracy is proven through experiment. Bond graph techniques are used to generate the state space model of the multi-actuator deformable mirror including piezo-electric actuator dynamics. Using this verified model, a robust multi-input multi-output (MIMO) H ∞ controller is designed and implemented. This controller proved superior performance as compared to a standard proportional-integral controller (PI) design.« less

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.

Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

NASA Technical Reports Server (NTRS)

Kaneshige, John T.; Campbell, Stefan Forrest

2009-01-01

The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC

Optical fiber pressure sensors for adaptive wings

NASA Astrophysics Data System (ADS)

Duncan, Paul G.; Jones, Mark E.; Shinpaugh, Kevin A.; Poland, Stephen H.; Murphy, Kent A.; Claus, Richard O.

1997-06-01

Optical fiber pressure sensors have been developed for use on a structurally-adaptive `smart wing'; further details of the design, fabrication and testing of the smart wing concept are presented in companion papers. This paper describes the design, construction, and performance of the pressure sensor and a combined optical and electronic signal processing system implemented to permit the measurement of a large number of sensors distributed over the control surfaces of a wing. Optical fiber pressure sensors were implemented due to anticipated large electromagnetic interference signals within the operational environment. The sensors utilized the principle of the extrinsic Fabry-Perot interferometer (EFPI) already developed for the measurement of strain and temperature. Here, the cavity is created inside a micromachined hollow-core tube with a silicon diaphragm at one end. The operation of the sensor is similar to that of the EFPI strain gage also discussed in several papers at this conference. The limitations placed upon the performance of the digital signal processing system were determined by the required pressure range of the sensors and the cycle time of the control system used to adaptively modify the shape of the wing. Sensor calibration and the results of testing performed are detailed.

Adaptive control of a Stewart platform-based manipulator

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Antrazi, Sami S.; Zhou, Zhen-Lei; Campbell, Charles E., Jr.

1993-01-01

A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

Velocity-free attitude coordinated tracking control for spacecraft formation flying.

PubMed

Hu, Qinglei; Zhang, Jian; Zhang, Youmin

2018-02-01

This article investigates the velocity-free attitude coordinated tracking control scheme for a group of spacecraft with the assumption that the angular velocities of the formation members are not available in control feedback. Initially, an angular velocity observer is constructed based on each individual's attitude quarternion. Then, the distributed attitude coordinated control law is designed by using the observed states, in which adaptive control method is adopted to handle the external disturbances. Stability of the overall closed-loop system is analyzed theoretically, which shows the system trajectory converges to a small set around origin with fast convergence rate. Numerical simulations are performed to demonstrate fast convergence and improved tracking performance of the proposed control strategy. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Dual-arm manipulators with adaptive control

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1991-01-01

The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1995-01-01

The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

Fast adaptive composite grid methods on distributed parallel architectures

NASA Technical Reports Server (NTRS)

Lemke, Max; Quinlan, Daniel

1992-01-01

The fast adaptive composite (FAC) grid method is compared with the adaptive composite method (AFAC) under variety of conditions including vectorization and parallelization. Results are given for distributed memory multiprocessor architectures (SUPRENUM, Intel iPSC/2 and iPSC/860). It is shown that the good performance of AFAC and its superiority over FAC in a parallel environment is a property of the algorithm and not dependent on peculiarities of any machine.

Effects of inter-packet spacing on the delivery of multimedia content

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

Kapadia, A. C.; Feng, A. C.; Feng, W. C.

2001-01-01

Streaming multimedia content with UDP has become increasingly popular over distributed systems such as the Internet. However, because UDP does not possess any congestion-control mechanism and most best-effort trafic is served by the congestion-controlled TCP, UDP flows steal bandwidth from TCP to the point that TCP flows can starve for network resources. Furthermore, such applications may cause the Internet infrastructure to eventually suffer from congestion collapse because UDP trafic does not self-regulate itself. To address this problem, next-generation Internet routers will implement active queue-management schemes to punish malicious traffic, e.g., non-adaptive UDP flows, and to the improve the performance ofmore » congestion-controlled traffic, e.g., TCP flows. The arrival of such routers will cripple the performance of today's UDP-based multimedia applications. So, in this paper, we introduce the notion of inter-packet spacing with control feedback to enable these UDP-based applications to perform well in the next-generation Internet while being adaptive and self-regulating. When compared with traditional UDP-based multimedia streaming, we illustrate that our counterintuitive, interpacket-spacing scheme with control feedback can reduce packet loss by 90% without adversely affecting delivered throughput. Keywords: network protocol, multimedia, packet spacing, rate-adjusting congestion control.« less

A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

USGS Publications Warehouse

Tsehaye, Iyob; Jones, Michael L.; Irwin, Brian J.; Fielder, David G.; Breck, James E.; Luukkonen, David R.

2015-01-01

The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

Autonomous distributed self-organization for mobile wireless sensor networks.

PubMed

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

PubMed Central

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-01-01

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450

An adaptive supervisory sliding fuzzy cerebellar model articulation controller for sensorless vector-controlled induction motor drive systems.

PubMed

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-03-25

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes--the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC--were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.

2011-01-01

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

In this paper, a novel adaptive control allocation framework is proposed. In the adaptive control allocation structure, cooperative actuators are grouped and treated as an equivalent control effector. A state feedback adaptive control signal is designed for the equivalent effector and allocated to the member actuators adaptively. Two adaptive control allocation algorithms are proposed, which guarantee closed-loop stability and asymptotic state tracking in the presence of uncertain loss of effectiveness and constant-magnitude actuator failures. The proposed algorithms can be shown to reduce the controller complexity with proper grouping of the actuators. The proposed adaptive control allocation schemes are applied to two linearized aircraft models, and the simulation results demonstrate the performance of the proposed algorithms.

Niche specialization of terrestrial archaeal ammonia oxidizers.

PubMed

Gubry-Rangin, Cécile; Hai, Brigitte; Quince, Christopher; Engel, Marion; Thomson, Bruce C; James, Phillip; Schloter, Michael; Griffiths, Robert I; Prosser, James I; Nicol, Graeme W

2011-12-27

Soil pH is a major determinant of microbial ecosystem processes and potentially a major driver of evolution, adaptation, and diversity of ammonia oxidizers, which control soil nitrification. Archaea are major components of soil microbial communities and contribute significantly to ammonia oxidation in some soils. To determine whether pH drives evolutionary adaptation and community structure of soil archaeal ammonia oxidizers, sequences of amoA, a key functional gene of ammonia oxidation, were examined in soils at global, regional, and local scales. Globally distributed database sequences clustered into 18 well-supported phylogenetic lineages that dominated specific soil pH ranges classified as acidic (pH <5), acido-neutral (5 ≤ pH <7), or alkalinophilic (pH ≥ 7). To determine whether patterns were reproduced at regional and local scales, amoA gene fragments were amplified from DNA extracted from 47 soils in the United Kingdom (pH 3.5-8.7), including a pH-gradient formed by seven soils at a single site (pH 4.5-7.5). High-throughput sequencing and analysis of amoA gene fragments identified an additional, previously undiscovered phylogenetic lineage and revealed similar pH-associated distribution patterns at global, regional, and local scales, which were most evident for the five most abundant clusters. Archaeal amoA abundance and diversity increased with soil pH, which was the only physicochemical characteristic measured that significantly influenced community structure. These results suggest evolution based on specific adaptations to soil pH and niche specialization, resulting in a global distribution of archaeal lineages that have important consequences for soil ecosystem function and nitrogen cycling.

Population differentiation in a Mediterranean relict shrub: the potential role of local adaptation for coping with climate change.

PubMed

Lázaro-Nogal, Ana; Matesanz, Silvia; Hallik, Lea; Krasnova, Alisa; Traveset, Anna; Valladares, Fernando

2016-04-01

Plants can respond to climate change by either migrating, adapting to the new conditions or going extinct. Relict plant species of limited distribution can be especially vulnerable as they are usually composed of small and isolated populations, which may reduce their ability to cope with rapidly changing environmental conditions. The aim of this study was to assess the vulnerability of Cneorum tricoccon L. (Cneoraceae), a Mediterranean relict shrub of limited distribution, to a future drier climate. We evaluated population differentiation in functional traits related to drought tolerance across seven representative populations of the species' range. We measured morphological and physiological traits in both the field and the greenhouse under three water availability levels. Large phenotypic differences among populations were found under field conditions. All populations responded plastically to simulated drought, but they differed in mean trait values as well as in the slope of the phenotypic response. Particularly, dry-edge populations exhibited multiple functional traits that favored drought tolerance, such as more sclerophyllous leaves, strong stomatal control but high photosynthetic rates, which increases water use efficiency (iWUE), and an enhanced ability to accumulate sugars as osmolytes. Although drought decreased RGR in all populations, this reduction was smaller for populations from the dry edge. Our results suggest that dry-edge populations of this relict species are well adapted to drought, which could potentially mitigate the species' extinction risk under drier scenarios. Dry-edge populations not only have a great conservation value but can also change expectations from current species' distribution models.

Decentralized Control of Scheduling in Distributed Systems.

DTIC Science & Technology

1983-03-18

the job scheduling algorithm adapts to the changing busyness of the various hosts in the system. The environment in which the job scheduling entities...resources and processes that constitute the node and a set of interfaces for accessing these processes and resources. The structure of a node could change ...parallel. Chang [CHNG82] has also described some algorithms for detecting properties of general graphs by traversing paths in a graph in parallel. One of

Development of a Distributed, Adaptive, Direction and Control (Civil Preparedness Communications) Network within the State of Rhode Island, Which May Serve as a Prototype Model for the Design of State Area Networks in Other States.

DTIC Science & Technology

1981-03-01

realize that a Civil Defense Communications capabil- ity existed, even in the best equipped communities. Notably, Town Council Presidents, Mayors ...5) B-; (6) AUDIO INPUT. Radios shall be furnished with mating conectors to accomplish , i.e.:(Molex male and female 10 PIN, or similar plugs.) All

Neural network based adaptive control for nonlinear dynamic regimes

NASA Astrophysics Data System (ADS)

Shin, Yoonghyun

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

Real-time performance assessment and adaptive control for a water chiller unit in an HVAC system

NASA Astrophysics Data System (ADS)

Bai, Jianbo; Li, Yang; Chen, Jianhao

2018-02-01

The paper proposes an adaptive control method for a water chiller unit in a HVAC system. Based on the minimum variance evaluation, the adaptive control method was used to realize better control of the water chiller unit. To verify the performance of the adaptive control method, the proposed method was compared with an a conventional PID controller, the simulation results showed that adaptive control method had superior control performance to that of the conventional PID controller.

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

PubMed Central

Kopp, Michael; Hermisson, Joachim

2009-01-01

We consider a population that adapts to a gradually changing environment. Our aim is to describe how ecological and genetic factors combine to determine the genetic basis of adaptation. Specifically, we consider the evolution of a polygenic trait that is under stabilizing selection with a moving optimum. The ecological dynamics are defined by the strength of selection, \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}{\\mathrm{\\tilde {{\\sigma}}}}\\end{equation*}\\end{document}, and the speed of the optimum, \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}\\tilde {{\\upsilon}}\\end{equation*}\\end{document}; the key genetic parameters are the mutation rate Θ and the variance of the effects of new mutations, ω. We develop analytical approximations within an “adaptive-walk” framework and describe how selection acts as a sieve that transforms a given distribution of new mutations into the distribution of adaptive substitutions. Our analytical results are complemented by individual-based simulations. We find that (i) the ecological dynamics have a strong effect on the distribution of adaptive substitutions and their impact depends largely on a single composite measure \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\usepackage[Euler]{upgreek} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin{equation*}{\\mathrm{{\\gamma}}}=\\tilde {{\\upsilon}}/({\\mathrm{\\tilde {{\\sigma}}}}{\\Theta}{\\mathrm{{\\omega}}}^{3})\\end{equation*}\\end{document}, which combines the ecological and genetic parameters; (ii) depending on γ, we can distinguish two distinct adaptive regimes: for large γ the adaptive process is mutation limited and dominated by genetic constraints, whereas for small γ it is environmentally limited and dominated by the external ecological dynamics; (iii) deviations from the adaptive-walk approximation occur for large mutation rates, when different mutant alleles interact via linkage or epistasis; and (iv) in contrast to predictions from previous models assuming constant selection, the distribution of adaptive substitutions is generally not exponential. PMID:19805820

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

Inverse dynamics of adaptive structures used as space cranes

NASA Technical Reports Server (NTRS)

Das, S. K.; Utku, S.; Wada, B. K.

1990-01-01

As a precursor to the real-time control of fast moving adaptive structures used as space cranes, a formulation is given for the flexibility induced motion relative to the nominal motion (i.e., the motion that assumes no flexibility) and for obtaining the open loop time varying driving forces. An algorithm is proposed for the computation of the relative motion and driving forces. The governing equations are given in matrix form with explicit functional dependencies. A simulator is developed to implement the algorithm on a digital computer. In the formulations, the distributed mass of the crane is lumped by two schemes, vz., 'trapezoidal' lumping and 'Simpson's rule' lumping. The effects of the mass lumping schemes are shown by simulator runs.

Embodying a cognitive model in a mobile robot

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Lonsdale, Deryle

2006-10-01

The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

[Transcultural adaptation of the Antifat Attitudes Test to Brazilian Portuguese].

PubMed

Obara, Angélica Almeida; Alvarenga, Marle Dos Santos

2018-05-01

Obese individuals are often blamed for their own condition and the targets of discrimination and prejudice. The scope of this study is to describe the cross-cultural adaptation to Brazilian Portuguese and the validation of the Antifat Attitudes Test - specifically developed for evaluation of negative attitudes toward the obese individual. The scale has 34 statements distributed in three subscales - Social/Character Disparagement (15 items), Physical/Romantic Unattractiveness (10 items) and Weight Control/Blame (9 items). The method involved the translation of the scale; evaluation of the conceptual, operational and item equivalence; evaluation of the semantic equivalence using the paired t test, the Pearson correlation coefficient and the intraclass correlation coefficient (ICC); internal consistency evaluation (Cronbach's alpha) and test-retest reliability (ICC) and Confirmatory Factor Analysis - after application in 340 college students in the area of health. The results showed good global internal consistency and reliability (α 0.85; CCI 0.83), and factor analysis showed that the original subscales can be kept in the adaptation, and therefore the scale adapted to the Brazilian-Portuguese version is valid and useful in studies to explore negative attitudes toward obese individuals.

A Step Towards Developing Adaptive Robot-Mediated Intervention Architecture (ARIA) for Children With Autism

PubMed Central

Bekele, Esubalew T; Lahiri, Uttama; Swanson, Amy R.; Crittendon, Julie A.; Warren, Zachary E.; Sarkar, Nilanjan

2013-01-01

Emerging technology, especially robotic technology, has been shown to be appealing to children with autism spectrum disorders (ASD). Such interest may be leveraged to provide repeatable, accurate and individualized intervention services to young children with ASD based on quantitative metrics. However, existing robot-mediated systems tend to have limited adaptive capability that may impact individualization. Our current work seeks to bridge this gap by developing an adaptive and individualized robot-mediated technology for children with ASD. The system is composed of a humanoid robot with its vision augmented by a network of cameras for real-time head tracking using a distributed architecture. Based on the cues from the child’s head movement, the robot intelligently adapts itself in an individualized manner to generate prompts and reinforcements with potential to promote skills in the ASD core deficit area of early social orienting. The system was validated for feasibility, accuracy, and performance. Results from a pilot usability study involving six children with ASD and a control group of six typically developing (TD) children are presented. PMID:23221831

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.

Autoadaptivity and optimization in distributed ECG interpretation.

PubMed

Augustyniak, Piotr

2010-03-01

This paper addresses principal issues of the ECG interpretation adaptivity in a distributed surveillance network. In the age of pervasive access to wireless digital communication, distributed biosignal interpretation networks may not only optimally solve difficult medical cases, but also adapt the data acquisition, interpretation, and transmission to the variable patient's status and availability of technical resources. The background of such adaptivity is the innovative use of results from the automatic ECG analysis to the seamless remote modification of the interpreting software. Since the medical relevance of issued diagnostic data depends on the patient's status, the interpretation adaptivity implies the flexibility of report content and frequency. Proposed solutions are based on the research on human experts behavior, procedures reliability, and usage statistics. Despite the limited scale of our prototype client-server application, the tests yielded very promising results: the transmission channel occupation was reduced by 2.6 to 5.6 times comparing to the rigid reporting mode and the improvement of the remotely computed diagnostic outcome was achieved in case of over 80% of software adaptation attempts.

Multi-Time Step Service Restoration for Advanced Distribution Systems and Microgrids

DOE PAGES

Chen, Bo; Chen, Chen; Wang, Jianhui; ...

2017-07-07

Modern power systems are facing increased risk of disasters that can cause extended outages. The presence of remote control switches (RCSs), distributed generators (DGs), and energy storage systems (ESS) provides both challenges and opportunities for developing post-fault service restoration methodologies. Inter-temporal constraints of DGs, ESS, and loads under cold load pickup (CLPU) conditions impose extra complexity on problem formulation and solution. In this paper, a multi-time step service restoration methodology is proposed to optimally generate a sequence of control actions for controllable switches, ESSs, and dispatchable DGs to assist the system operator with decision making. The restoration sequence is determinedmore » to minimize the unserved customers by energizing the system step by step without violating operational constraints at each time step. The proposed methodology is formulated as a mixed-integer linear programming (MILP) model and can adapt to various operation conditions. Furthermore, the proposed method is validated through several case studies that are performed on modified IEEE 13-node and IEEE 123-node test feeders.« less

A New Adaptive Self-Tuning Fourier Coefficients Algorithm for Periodic Torque Ripple Minimization in Permanent Magnet Synchronous Motors (PMSM)

PubMed Central

Gómez-Espinosa, Alfonso; Hernández-Guzmán, Víctor M.; Bandala-Sánchez, Manuel; Jiménez-Hernández, Hugo; Rivas-Araiza, Edgar A.; Rodríguez-Reséndiz, Juvenal; Herrera-Ruíz, Gilberto

2013-01-01

Torque ripple occurs in Permanent Magnet Synchronous Motors (PMSMs) due to the non-sinusoidal flux density distribution around the air-gap and variable magnetic reluctance of the air-gap due to the stator slots distribution. These torque ripples change periodically with rotor position and are apparent as speed variations, which degrade the PMSM drive performance, particularly at low speeds, because of low inertial filtering. In this paper, a new self-tuning algorithm is developed for determining the Fourier Series Controller coefficients with the aim of reducing the torque ripple in a PMSM, thus allowing for a smoother operation. This algorithm adjusts the controller parameters based on the component's harmonic distortion in time domain of the compensation signal. Experimental evaluation is performed on a DSP-controlled PMSM evaluation platform. Test results obtained validate the effectiveness of the proposed self-tuning algorithm, with the Fourier series expansion scheme, in reducing the torque ripple. PMID:23519345

Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

DOE PAGES

Bracale, Antonio; Barros, Julio; Cacciapuoti, Angela Sara; ...

2015-06-10

Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users andmore » vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.« less

Multi-Time Step Service Restoration for Advanced Distribution Systems and Microgrids

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

Chen, Bo; Chen, Chen; Wang, Jianhui

Modern power systems are facing increased risk of disasters that can cause extended outages. The presence of remote control switches (RCSs), distributed generators (DGs), and energy storage systems (ESS) provides both challenges and opportunities for developing post-fault service restoration methodologies. Inter-temporal constraints of DGs, ESS, and loads under cold load pickup (CLPU) conditions impose extra complexity on problem formulation and solution. In this paper, a multi-time step service restoration methodology is proposed to optimally generate a sequence of control actions for controllable switches, ESSs, and dispatchable DGs to assist the system operator with decision making. The restoration sequence is determinedmore » to minimize the unserved customers by energizing the system step by step without violating operational constraints at each time step. The proposed methodology is formulated as a mixed-integer linear programming (MILP) model and can adapt to various operation conditions. Furthermore, the proposed method is validated through several case studies that are performed on modified IEEE 13-node and IEEE 123-node test feeders.« less

Self-adaptive demodulation for polarization extinction ratio in distributed polarization coupling.

PubMed

Zhang, Hongxia; Ren, Yaguang; Liu, Tiegen; Jia, Dagong; Zhang, Yimo

2013-06-20

A self-adaptive method for distributed polarization extinction ratio (PER) demodulation is demonstrated. It is characterized by dynamic PER threshold coupling intensity (TCI) and nonuniform PER iteration step length (ISL). Based on the preset PER calculation accuracy and original distribution coupling intensity, TCI and ISL can be made self-adaptive to determine contributing coupling points inside the polarizing devices. Distributed PER is calculated by accumulating those coupling points automatically and selectively. Two different kinds of polarization-maintaining fibers are tested, and PERs are obtained after merely 3-5 iterations using the proposed method. Comparison experiments with Thorlabs commercial instrument are also conducted, and results show high consistency. In addition, the optimum preset PER calculation accuracy of 0.05 dB is obtained through many repeated experiments.

Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects

PubMed Central

2016-01-01

Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments. PMID:26990188

An integrated utility-based model of conflict evaluation and resolution in the Stroop task.

PubMed

Chuderski, Adam; Smolen, Tomasz

2016-04-01

Cognitive control allows humans to direct and coordinate their thoughts and actions in a flexible way, in order to reach internal goals regardless of interference and distraction. The hallmark test used to examine cognitive control is the Stroop task, which elicits both the weakly learned but goal-relevant and the strongly learned but goal-irrelevant response tendencies, and requires people to follow the former while ignoring the latter. After reviewing the existing computational models of cognitive control in the Stroop task, its novel, integrated utility-based model is proposed. The model uses 3 crucial control mechanisms: response utility reinforcement learning, utility-based conflict evaluation using the Festinger formula for assessing the conflict level, and top-down adaptation of response utility in service of conflict resolution. Their complex, dynamic interaction led to replication of 18 experimental effects, being the largest data set explained to date by 1 Stroop model. The simulations cover the basic congruency effects (including the response latency distributions), performance dynamics and adaptation (including EEG indices of conflict), as well as the effects resulting from manipulations applied to stimulation and responding, which are yielded by the extant Stroop literature. (c) 2016 APA, all rights reserved).

A Minimal Model Describing Hexapedal Interlimb Coordination: The Tegotae-Based Approach

PubMed Central

Owaki, Dai; Goda, Masashi; Miyazawa, Sakiko; Ishiguro, Akio

2017-01-01

Insects exhibit adaptive and versatile locomotion despite their minimal neural computing. Such locomotor patterns are generated via coordination between leg movements, i.e., an interlimb coordination, which is largely controlled in a distributed manner by neural circuits located in thoracic ganglia. However, the mechanism responsible for the interlimb coordination still remains elusive. Understanding this mechanism will help us to elucidate the fundamental control principle of animals' agile locomotion and to realize robots with legs that are truly adaptive and could not be developed solely by conventional control theories. This study aims at providing a “minimal" model of the interlimb coordination mechanism underlying hexapedal locomotion, in the hope that a single control principle could satisfactorily reproduce various aspects of insect locomotion. To this end, we introduce a novel concept we named “Tegotae,” a Japanese concept describing the extent to which a perceived reaction matches an expectation. By using the Tegotae-based approach, we show that a surprisingly systematic design of local sensory feedback mechanisms essential for the interlimb coordination can be realized. We also use a hexapod robot we developed to show that our mathematical model of the interlimb coordination mechanism satisfactorily reproduces various insects' gait patterns. PMID:28649197

Congestion control for a fair packet delivery in WSN: from a complex system perspective.

PubMed

Aguirre-Guerrero, Daniela; Marcelín-Jiménez, Ricardo; Rodriguez-Colina, Enrique; Pascoe-Chalke, Michael

2014-01-01

In this work, we propose that packets travelling across a wireless sensor network (WSN) can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.

PADF electromagnetic source localization using extremum seeking control

NASA Astrophysics Data System (ADS)

Al Issa, Huthaifa A.; Ordóñez, Raúl

2014-10-01

Wireless Sensor Networks (WSNs) are a significant technology attracting considerable research interest. Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power and multi-functional sensors that are small in size and communicate over short distances. Most WSN applications require knowing or measuring locations of thousands of sensors accurately. For example, sensing data without knowing the sensor location is often meaningless. Locations of sensor nodes are fundamental to providing location stamps, locating and tracking objects, forming clusters, and facilitating routing. This research focused on the modeling and implementation of distributed, mobile radar sensor networks. In particular, we worked on the problem of Position-Adaptive Direction Finding (PADF), to determine the location of a non- collaborative transmitter, possibly hidden within a structure, by using a team of cooperative intelligent sensor networks. Position-Adaptive radar concepts have been formulated and investigated at the Air Force Research Laboratory (AFRL) within the past few years. In this paper, we present the simulation performance analysis on the application aspect. We apply Extremum Seeking Control (ESC) schemes by using the swarm seeking problem, where the goal is to design a control law for each individual sensor that can minimize the error metric by adapting the sensor positions in real-time, thereby minimizing the unknown estimation error. As a result we achieved source seeking and collision avoidance of the entire group of the sensor positions.

Transitioning Active Flow Control to Applications

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Horta, Lucas G.; Chen, Fang-Jenq

1999-01-01

Active Flow Control Programs at NASA, the U.S. Air Force, and DARPA have been initiated with the goals of obtaining revolutionary advances in aerodynamic performance and maneuvering compared to conventional approaches. These programs envision the use of actuators, sensors, and controllers on applications such as aircraft wings/tails, engine nacelles, internal ducts, nozzles, projectiles, weapons bays, and hydrodynamic vehicles. Anticipated benefits of flow control include reduced weight, part count, and operating cost and reduced fuel burn (and emissions), noise and enhanced safety if the sensors serve a dual role of flow control and health monitoring. To get from the bench-top or laboratory test to adaptive distributed control systems on realistic applications, reliable validated design tools are needed in addition to sub- and large-scale wind-tunnel and flight experiments. This paper will focus on the development of tools for active flow control applications.

Numerical design of an adaptive aileron

NASA Astrophysics Data System (ADS)

Amendola, Gianluca; Dimino, Ignazio; Concilio, Antonio; Magnifico, Marco; Pecora, Rosario

2016-04-01

The study herein described is aimed at investigating the feasibility of an innovative full-scale camber morphing aileron device. In the framework of the "Adaptive Aileron" project, an international cooperation between Italy and Canada, this goal was carried out with the integration of different morphing concepts in a wing-tip prototype. As widely demonstrated in recent European projects such as Clean Sky JTI and SARISTU, wing trailing edge morphing may lead to significant drag reduction (up to 6%) in off-design flight points by adapting chord-wise camber variations in cruise to compensate A/C weight reduction following fuel consumption. Those researches focused on the flap region as the most immediate solution to implement structural adaptations. However, there is also a growing interest in extending morphing functionalities to the aileron region preserving its main functionality in controlling aircraft directional stability. In fact, the external region of the wing seems to be the most effective in producing "lift over drag" improvements by morphing. Thus, the objective of the presented research is to achieve a certain drag reduction in off-design flight points by adapting wing shape and lift distribution following static deflections. In perspective, the developed device could also be used as a load alleviation system to reduce gust effects, augmenting its frequency bandwidth. In this paper, the preliminary design of the adaptive aileron is first presented, assessed on the base of the external aerodynamic loads. The primary structure is made of 5 segmented ribs, distributed along 4 bays, each splitted into three consecutive parts, connected with spanwise stringers. The aileron shape modification is then implemented by means of an actuation system, based on a classical quick-return mechanism, opportunely suited for the presented application. Finite element analyses were assessed for properly sizing the load-bearing structure and actuation systems and for characterizing their dynamic behavior. Obtained results are reported and widely discussed.

Was RA Fisher Right?

PubMed

Srivastava, Ayush; Srivastava, Anurag; Pandey, Ravindra M

2017-10-01

Randomized controlled trials have become the most respected scientific tool to measure the effectiveness of a medical therapy. The design, conduct and analysis of randomized controlled trials were developed by Sir Ronald A. Fisher, a mathematician in Great Britain. Fisher propounded that the process of randomization would equally distribute all the known and even unknown covariates in the two or more comparison groups, so that any difference observed could be ascribed to treatment effect. Today, we observe that in many situations, this prediction of Fisher does not stand true; hence, adaptive randomization schedules have been designed to adjust for major imbalance in important covariates. Present essay unravels some weaknesses inherent in Fisherian concept of randomized controlled trial.

76 FR 60006 - Joint Europe Africa Deployment & Distribution Conference 2011: “Adapting To Challenge and Change”

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... DEPARTMENT OF DEFENSE Office of the Secretary Joint Europe Africa Deployment & Distribution Conference 2011: ``Adapting To Challenge and Change'' AGENCY: United States Africa Command, Department of Defense (DoD). ACTION: Notice of conference. SUMMARY: This document announces that U.S. Africa Command...

Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning

ERIC Educational Resources Information Center

Deng, Lawrence Y.; Keh, Huan-Chao; Liu, Yi-Jen

2010-01-01

More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model.…

Robust adaptive vibration control of a flexible structure.

PubMed

Khoshnood, A M; Moradi, H M

2014-07-01

Different types of L1 adaptive control systems show that using robust theories with adaptive control approaches has produced high performance controllers. In this study, a model reference adaptive control scheme considering robust theories is used to propose a practical control system for vibration suppression of a flexible launch vehicle (FLV). In this method, control input of the system is shaped from the dynamic model of the vehicle and components of the control input are adaptively constructed by estimating the undesirable vibration frequencies. Robust stability of the adaptive vibration control system is guaranteed by using the L1 small gain theorem. Simulation results of the robust adaptive vibration control strategy confirm that the effects of vibration on the vehicle performance considerably decrease without the loss of the phase margin of the system. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive linear rank tests for eQTL studies

PubMed Central

Szymczak, Silke; Scheinhardt, Markus O.; Zeller, Tanja; Wild, Philipp S.; Blankenberg, Stefan; Ziegler, Andreas

2013-01-01

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal–Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. PMID:22933317

Adaptive linear rank tests for eQTL studies.

PubMed

Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

2013-02-10

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

Planform, aero-structural, and flight control optimization for tailless morphing aircraft

NASA Astrophysics Data System (ADS)

Molinari, Giulio; Arrieta, Andres F.; Ermanni, Paolo

2015-04-01

Tailless airplanes with swept wings rely on variations of the spanwise lift distribution to provide controllability in roll, pitch and yaw. Conventionally, this is achieved utilizing multiple control surfaces, such as elevons, on the wing trailing edge. As every flight condition requires different control moments (e.g. to provide pitching moment equilibrium), these surfaces are practically permanently displaced. Due to their nature, causing discontinuities, corners and gaps, they bear aerodynamic penalties, mostly in terms of shape drag. Shape adaptation, by means of chordwise morphing, has the potential of varying the lift of a wing section by deforming its profile in a way that minimizes the resulting drag. Furthermore, as the shape can be varied differently along the wingspan, the lift distribution can be tailored to each specific flight condition. For this reason, tailless aircraft appear as a prime choice to apply morphing techniques, as the attainable benefits are potentially significant. In this work, we present a methodology to determine the optimal planform, profile shape, and morphing structure for a tailless aircraft. The employed morphing concept is based on a distributed compliance structure, actuated by Macro Fiber Composite (MFC) piezoelectric elements. The multidisciplinary optimization is performed considering the static and dynamic aeroelastic behavior of the resulting structure. The goal is the maximization of the aerodynamic efficiency while guaranteeing the controllability of the plane, by means of morphing, in a set of flight conditions.

Automatic motor task selection via a bandit algorithm for a brain-controlled button

NASA Astrophysics Data System (ADS)

Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

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.

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

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

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 second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

A 3D isodose manipulation tool for interactive dose shaping

NASA Astrophysics Data System (ADS)

Kamerling, C. P.; Ziegenhein, P.; Heinrich, H.; Oelfke, U.

2014-03-01

The interactive dose shaping (IDS) planning paradigm aims to perform interactive local dose adaptations of an IMRT plan without compromising already established valuable dose features in real-time. In this work we introduce an interactive 3D isodose manipulation tool which enables local modifications of a dose distribution intuitively by direct manipulation of an isodose surface. We developed an in-house IMRT TPS framework employing an IDS engine as well as a 3D GUI for dose manipulation and visualization. In our software an initial dose distribution can be interactively modified through an isodose surface manipulation tool by intuitively clicking on an isodose surface. To guide the user interaction, the position of the modification is indicated by a sphere while the mouse cursor hovers the isodose surface. The sphere's radius controls the locality of the modification. The tool induces a dose modification as a direct change of dose in one or more voxels, which is incrementally obtained by fluence adjustments. A subsequent recovery step identifies voxels with violated dose features and aims to recover their original dose. We showed a proof of concept study for the proposed tool by adapting the dose distribution of a prostate case (9 beams, coplanar). Single dose modifications take less than 2 seconds on an actual desktop PC.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

PubMed

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

Graphical models for optimal power flow

DOE PAGES

Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; ...

2016-09-13

Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithmmore » for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.« less

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Adaptive neural network motion control for aircraft under uncertainty conditions

NASA Astrophysics Data System (ADS)

Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

2018-02-01

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Structural optimization of 3D-printed synthetic spider webs for high strength

PubMed Central

Qin, Zhao; Compton, Brett G.; Lewis, Jennifer A.; Buehler, Markus J.

2015-01-01

Spiders spin intricate webs that serve as sophisticated prey-trapping architectures that simultaneously exhibit high strength, elasticity and graceful failure. To determine how web mechanics are controlled by their topological design and material distribution, here we create spider-web mimics composed of elastomeric filaments. Specifically, computational modelling and microscale 3D printing are combined to investigate the mechanical response of elastomeric webs under multiple loading conditions. We find the existence of an asymptotic prey size that leads to a saturated web strength. We identify pathways to design elastomeric material structures with maximum strength, low density and adaptability. We show that the loading type dictates the optimal material distribution, that is, a homogeneous distribution is better for localized loading, while stronger radial threads with weaker spiral threads is better for distributed loading. Our observations reveal that the material distribution within spider webs is dictated by the loading condition, shedding light on their observed architectural variations. PMID:25975372

RTDS implementation of an improved sliding mode based inverter controller for PV system.

PubMed

Islam, Gazi; Muyeen, S M; Al-Durra, Ahmed; Hasanien, Hany M

2016-05-01

This paper proposes a novel approach for testing dynamics and control aspects of a large scale photovoltaic (PV) system in real time along with resolving design hindrances of controller parameters using Real Time Digital Simulator (RTDS). In general, the harmonic profile of a fast controller has wide distribution due to the large bandwidth of the controller. The major contribution of this paper is that the proposed control strategy gives an improved voltage harmonic profile and distribute it more around the switching frequency along with fast transient response; filter design, thus, becomes easier. The implementation of a control strategy with high bandwidth in small time steps of Real Time Digital Simulator (RTDS) is not straight forward. This paper shows a good methodology for the practitioners to implement such control scheme in RTDS. As a part of the industrial process, the controller parameters are optimized using particle swarm optimization (PSO) technique to improve the low voltage ride through (LVRT) performance under network disturbance. The response surface methodology (RSM) is well adapted to build analytical models for recovery time (Rt), maximum percentage overshoot (MPOS), settling time (Ts), and steady state error (Ess) of the voltage profile immediate after inverter under disturbance. A systematic approach of controller parameter optimization is detailed. The transient performance of the PSO based optimization method applied to the proposed sliding mode controlled PV inverter is compared with the results from genetic algorithm (GA) based optimization technique. The reported real time implementation challenges and controller optimization procedure are applicable to other control applications in the field of renewable and distributed generation systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive powertrain control for plugin hybrid electric vehicles

DOEpatents

Kedar-Dongarkar, Gurunath; Weslati, Feisel

2013-10-15

A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition

NASA Technical Reports Server (NTRS)

Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu

2010-01-01

Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.

Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

PubMed Central

Murata, Masayuki

2013-01-01

The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

Quagga and zebra mussels: biology, impacts, and control

USGS Publications Warehouse

Nalepa, Thomas F.; Schloesser, Don W.; Nalepa, Thomas F.; Schloesser, Don W.

2013-01-01

Quagga and Zebra Mussels: Biology, Impacts, and Control, Second Edition provides a broad view of the zebra/quagga mussel issue, offering a historic perspective and up-to-date information on mussel research. Comprising 48 chapters, this second edition includes reviews of mussel morphology, physiology, and behavior. It details mussel distribution and spread in Europe and across North America, and examines policy and regulatory responses, management strategies, and mitigation efforts. In addition, this book provides extensive coverage of the impact of invasive mussel species on freshwater ecosystems, including effects on water clarity, phytoplankton, water quality, food web changes, and consequences to other aquatic fauna. It also reviews and offers new insights on how zebra and quagga mussels respond and adapt to varying environmental conditions. This new edition includes seven video clips that complement chapter text and, through visual documentation, provide a greater understanding of mussel behavior and distribution.

Enhancing performance of LCoS-SLM as adaptive optics by using computer-generated holograms modulation software

NASA Astrophysics Data System (ADS)

Tsai, Chun-Wei; Lyu, Bo-Han; Wang, Chen; Hung, Cheng-Chieh

2017-05-01

We have already developed multi-function and easy-to-use modulation software that was based on LabVIEW system. There are mainly four functions in this modulation software, such as computer generated holograms (CGH) generation, CGH reconstruction, image trimming, and special phase distribution. Based on the above development of CGH modulation software, we could enhance the performance of liquid crystal on silicon - spatial light modulator (LCoSSLM) as similar as the diffractive optical element (DOE) and use it on various adaptive optics (AO) applications. Through the development of special phase distribution, we are going to use the LCoS-SLM with CGH modulation software into AO technology, such as optical microscope system. When the LCOS-SLM panel is integrated in an optical microscope system, it could be placed on the illumination path or on the image forming path. However, LCOS-SLM provides a program-controllable liquid crystal array for optical microscope. It dynamically changes the amplitude or phase of light and gives the obvious advantage, "Flexibility", to the system

Distributions in the error space: goal-directed movements described in time and state-space representations.

PubMed

Fisher, Moria E; Huang, Felix C; Wright, Zachary A; Patton, James L

2014-01-01

Manipulation of error feedback has been of great interest to recent studies in motor control and rehabilitation. Typically, motor adaptation is shown as a change in performance with a single scalar metric for each trial, yet such an approach might overlook details about how error evolves through the movement. We believe that statistical distributions of movement error through the extent of the trajectory can reveal unique patterns of adaption and possibly reveal clues to how the motor system processes information about error. This paper describes different possible ordinate domains, focusing on representations in time and state-space, used to quantify reaching errors. We hypothesized that the domain with the lowest amount of variability would lead to a predictive model of reaching error with the highest accuracy. Here we showed that errors represented in a time domain demonstrate the least variance and allow for the highest predictive model of reaching errors. These predictive models will give rise to more specialized methods of robotic feedback and improve previous techniques of error augmentation.

Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, Celal

1991-01-01

The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

Adaptive allocation for binary outcomes using decreasingly informative priors.

PubMed

Sabo, Roy T

2014-01-01

A method of outcome-adaptive allocation is presented using Bayes methods, where a natural lead-in is incorporated through the use of informative yet skeptical prior distributions for each treatment group. These prior distributions are modeled on unobserved data in such a way that their influence on the allocation scheme decreases as the trial progresses. Simulation studies show this method to behave comparably to the Bayesian adaptive allocation method described by Thall and Wathen (2007), who incorporate a natural lead-in through sample-size-based exponents.

A novel composite adaptive flap controller design by a high-efficient modified differential evolution identification approach.

PubMed

Li, Nailu; Mu, Anle; Yang, Xiyun; Magar, Kaman T; Liu, Chao

2018-05-01

The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Interplay between population firing stability and single neuron dynamics in hippocampal networks

PubMed Central

Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna

2015-01-01

Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699

Model-based wavefront sensorless adaptive optics system for large aberrations and extended objects.

PubMed

Yang, Huizhen; Soloviev, Oleg; Verhaegen, Michel

2015-09-21

A model-based wavefront sensorless (WFSless) adaptive optics (AO) system with a 61-element deformable mirror is simulated to correct the imaging of a turbulence-degraded extended object. A fast closed-loop control algorithm, which is based on the linear relation between the mean square of the aberration gradients and the second moment of the image intensity distribution, is used to generate the control signals for the actuators of the deformable mirror (DM). The restoration capability and the convergence rate of the AO system are investigated with different turbulence strength wave-front aberrations. Simulation results show the model-based WFSless AO system can restore those images degraded by different turbulence strengths successfully and obtain the correction very close to the achievable capability of the given DM. Compared with the ideal correction of 61-element DM, the averaged relative error of RMS value is 6%. The convergence rate of AO system is independent of the turbulence strength and only depends on the number of actuators of DM.

Cerebellarlike corrective model inference engine for manipulation tasks.

PubMed

Luque, Niceto Rafael; Garrido, Jesús Alberto; Carrillo, Richard Rafael; Coenen, Olivier J-M D; Ros, Eduardo

2011-10-01

This paper presents how a simple cerebellumlike architecture can infer corrective models in the framework of a control task when manipulating objects that significantly affect the dynamics model of the system. The main motivation of this paper is to evaluate a simplified bio-mimetic approach in the framework of a manipulation task. More concretely, the paper focuses on how the model inference process takes place within a feedforward control loop based on the cerebellar structure and on how these internal models are built up by means of biologically plausible synaptic adaptation mechanisms. This kind of investigation may provide clues on how biology achieves accurate control of non-stiff-joint robot with low-power actuators which involve controlling systems with high inertial components. This paper studies how a basic temporal-correlation kernel including long-term depression (LTD) and a constant long-term potentiation (LTP) at parallel fiber-Purkinje cell synapses can effectively infer corrective models. We evaluate how this spike-timing-dependent plasticity correlates sensorimotor activity arriving through the parallel fibers with teaching signals (dependent on error estimates) arriving through the climbing fibers from the inferior olive. This paper addresses the study of how these LTD and LTP components need to be well balanced with each other to achieve accurate learning. This is of interest to evaluate the relevant role of homeostatic mechanisms in biological systems where adaptation occurs in a distributed manner. Furthermore, we illustrate how the temporal-correlation kernel can also work in the presence of transmission delays in sensorimotor pathways. We use a cerebellumlike spiking neural network which stores the corrective models as well-structured weight patterns distributed among the parallel fibers to Purkinje cell connections.

Flight Validation of a Metrics Driven L(sub 1) Adaptive Control

NASA Technical Reports Server (NTRS)

Dobrokhodov, Vladimir; Kitsios, Ioannis; Kaminer, Isaac; Jones, Kevin D.; Xargay, Enric; Hovakimyan, Naira; Cao, Chengyu; Lizarraga, Mariano I.; Gregory, Irene M.

2008-01-01

The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf AP with and without adaptive augmentation to recover from control surface failures.

Direct adaptive control of manipulators in Cartesian space

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

High Resolution Sensing and Control of Urban Water Networks

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Adaptive control of dual-arm robots

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

Three strategies for adaptive control of cooperative dual-arm robots are described. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through the load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions, while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. The controllers have simple structures and are computationally fast for on-line implementation with high sampling rates.

Flexible Two-Photon Interference Fringes with Thermal Light.

PubMed

Cao, De-Zhong; Ren, Cheng; Ni, Jin-Yang; Zhang, Yan; Zhang, Su-Heng; Wang, Kaige

2017-05-16

Flexible interference patterning is an important tool for adaptable measurement precisions. We report on experimental results of controllable two-photon interference fringes with thermal light in an incoherent rotational shearing interferometer. The two incoherent beams in the interferometer are orthogonally polarized, and their wavefront distributions differ only in an angle of rotation. The spacings and directions of the two-photon interference fringes vary with the rotation angle, as illustrated in three cases of two-photon correlation measurements in experiment.

Ecological variation in South American geophagine cichlids arose during an early burst of adaptive morphological and functional evolution

PubMed Central

Arbour, Jessica Hilary; López-Fernández, Hernán

2013-01-01

Diversity and disparity are unequally distributed both phylogenetically and geographically. This uneven distribution may be owing to differences in diversification rates between clades resulting from processes such as adaptive radiation. We examined the rate and distribution of evolution in feeding biomechanics in the extremely diverse and continentally distributed South American geophagine cichlids. Evolutionary patterns in multivariate functional morphospace were examined using a phylomorphospace approach, disparity-through-time analyses and by comparing Brownian motion (BM) and adaptive peak evolutionary models using maximum likelihood. The most species-rich and functionally disparate clade (CAS) expanded more efficiently in morphospace and evolved more rapidly compared with both BM expectations and its sister clade (GGD). Members of the CAS clade also exhibited an early burst in functional evolution that corresponds to the development of modern ecological roles and may have been related to the colonization of a novel adaptive peak characterized by fast oral jaw mechanics. Furthermore, reduced ecological opportunity following this early burst may have restricted functional evolution in the GGD clade, which is less species-rich and more ecologically specialized. Patterns of evolution in ecologically important functional traits are consistent with a pattern of adaptive radiation within the most diverse clade of Geophagini. PMID:23740780

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

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. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy.

PubMed

Morel, Paul; Wu, Xiaodong; Blin, Guillaume; Vialette, Stéphane; Flynn, Ryan; Hyer, Daniel; Wang, Dongxu

2015-01-01

This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution. The method proposed in this study adapts the weight (MU) of the delivering pencil beam to that of the target spot; it will actually hit during patient/target motion. The target spot that a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D) CT. After the adapted delivery, the required total weight [Monitor Unit (MU)] for this target spot is then subtracted from the planned value. With continuous patient motion and continuous spot scanning, the planned doses to all target spots will eventually be all fulfilled. In a proof-of-principle test, a lung case was presented with realistic temporal and motion parameters; the resultant dose distribution using spot weight adaptation was compared to that without using this method. The impact of the real-time patient/target position tracking or prediction was also investigated. For moderate motion (i.e., mean amplitude 0.5 cm), D95% to the planning target volume (PTV) was only 81.5% of the prescription (RX) dose; with spot weight adaptation PTV D95% achieves 97.7% RX. For large motion amplitude (i.e., 1.5 cm), without spot weight adaptation PTV D95% is only 42.9% of RX; with spot weight adaptation, PTV D95% achieves 97.7% RX. Larger errors in patient/target position tracking or prediction led to worse final target coverage; an error of 3 mm or smaller in patient/target position tracking is preferred. The proposed spot weight adaptation method was able to deliver the planned dose distribution and maintain target coverage when patient motion was involved. The successful implementation of this method would rely on accurate monitoring or prediction of patient/target motion.

Optimal Power Flow for Distribution Systems under Uncertain Forecasts: Preprint

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

2016-12-01

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

Fault Injection and Monitoring Capability for a Fault-Tolerant Distributed Computation System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo; Yates, Amy M.; Malekpour, Mahyar R.

2010-01-01

The Configurable Fault-Injection and Monitoring System (CFIMS) is intended for the experimental characterization of effects caused by a variety of adverse conditions on a distributed computation system running flight control applications. A product of research collaboration between NASA Langley Research Center and Old Dominion University, the CFIMS is the main research tool for generating actual fault response data with which to develop and validate analytical performance models and design methodologies for the mitigation of fault effects in distributed flight control systems. Rather than a fixed design solution, the CFIMS is a flexible system that enables the systematic exploration of the problem space and can be adapted to meet the evolving needs of the research. The CFIMS has the capabilities of system-under-test (SUT) functional stimulus generation, fault injection and state monitoring, all of which are supported by a configuration capability for setting up the system as desired for a particular experiment. This report summarizes the work accomplished so far in the development of the CFIMS concept and documents the first design realization.

Distributed Traffic Complexity Management by Preserving Trajectory Flexibility

NASA Technical Reports Server (NTRS)

Idris, Husni; Vivona, Robert A.; Garcia-Chico, Jose-Luis; Wing, David J.

2007-01-01

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which groundbased service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory-oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.

Fast spacecraft adaptive attitude tracking control through immersion and invariance design

NASA Astrophysics Data System (ADS)

Wen, Haowei; Yue, Xiaokui; Li, Peng; Yuan, Jianping

2017-10-01

This paper presents a novel non-certainty-equivalence adaptive control method for the attitude tracking control problem of spacecraft with inertia uncertainties. The proposed immersion and invariance (I&I) based adaptation law provides a more direct and flexible approach to circumvent the limitations of the basic I&I method without employing any filter signal. By virtue of the adaptation high-gain equivalence property derived from the proposed adaptive method, the closed-loop adaptive system with a low adaptation gain could recover the high adaptation gain performance of the filter-based I&I method, and the resulting control torque demands during the initial transient has been significantly reduced. A special feature of this method is that the convergence of the parameter estimation error has been observably improved by utilizing an adaptation gain matrix instead of a single adaptation gain value. Numerical simulations are presented to highlight the various benefits of the proposed method compared with the certainty-equivalence-based control method and filter-based I&I control schemes.

Decentralized adaptive control

NASA Technical Reports Server (NTRS)

Oh, B. J.; Jamshidi, M.; Seraji, H.

1988-01-01

A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

Experiments in structural dynamics and control using a grid

NASA Technical Reports Server (NTRS)

Montgomery, R. C.

1985-01-01

Future spacecraft are being conceived that are highly flexible and of extreme size. The two features of flexibility and size pose new problems in control system design. Since large scale structures are not testable in ground based facilities, the decision on component placement must be made prior to full-scale tests on the spacecraft. Control law research is directed at solving problems of inadequate modelling knowledge prior to operation required to achieve peak performance. Another crucial problem addressed is accommodating failures in systems with smart components that are physically distributed on highly flexible structures. Parameter adaptive control is a method of promise that provides on-orbit tuning of the control system to improve performance by upgrading the mathematical model of the spacecraft during operation. Two specific questions are answered in this work. They are: What limits does on-line parameter identification with realistic sensors and actuators place on the ultimate achievable performance of a system in the highly flexible environment? Also, how well must the mathematical model used in on-board analytic redundancy be known and what are the reasonable expectations for advanced redundancy management schemes in the highly flexible and distributed component environment?

Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.

PubMed

Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia; Huaipin Zhang; Dong Yue; Wei Zhao; Songlin Hu; Chunxia Dou; Hu, Songlin; Zhang, Huaipin; Dou, Chunxia; Yue, Dong; Zhao, Wei

2018-06-01

This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

Adaptive Decentralized Control

DTIC Science & Technology

1985-04-01

and implementation of the decentralized controllers. It raises, however, many difficult questions regarding the conditions under which such a scheme ...adaptive controller, and a general form of the model reference adaptive controller (4]. We believe that this work represents a significant advance in the...Comparing the adaptive system with the tuned system results in the development of a generic adaptive error system. Passivity theory was used to derive

Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator

NASA Technical Reports Server (NTRS)

Balas, Mark; Frost, Susan

2012-01-01

Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.

Climate change and animal health in Africa.

PubMed

Van den Bossche, P; Coetzer, J A W

2008-08-01

Climate change is expected to have direct and indirect impacts on African livestock. Direct impacts include increased ambient temperature, floods and droughts. Indirect impacts are the result of reduced availability of water and forage and changes in the environment that promote the spread of contagious diseases through increased contact between animals, or increased survival or availability of the agent or its intermediate host. The distribution and prevalence of vector-borne diseases may be the most significant effect of climate change. The potential vulnerability of the livestock industry will depend on its ability to adapt to such changes. Enhancing this adaptive capacity presents a practical way of coping with climate change. Adaptive capacity could be increased by enabling the African livestock owner to cope better with animal health problems through appropriate policy measures and institutional support. Developing an effective and sustainable animal health service, associated surveillance and emergency preparedness systems and sustainable disease control and prevention programmes is perhaps the most important strategy for dealing with climate change in many African countries.

Software-centric View on OVMS for LBT

NASA Astrophysics Data System (ADS)

Trowitzsch, J.; Borelli, J.; Pott, J.; Kürster, M.

2012-09-01

The performance of infrared interferometry (IF) and adaptive optics (AO) strongly depends on the mitigation and correction of telescope vibrations. Therefore, at the Large Binocular Telescope (LBT) the OVMS, the Optical Path Difference and Vibration Monitoring System, is being installed. It is meant to ensure suitable conditions for adaptive optics and interferometry. The vibration information is collected from accelerometers that are distributed over the optical elements of the LBT. The collected vibration measurements are converted into tip-tilt and optical path difference data. That data is utilized in the control strategies of the LBT adaptive secondary mirrors and the beam combining interferometers, LINC-NIRVANA and LBTI. Within the OVMS the software part is responsibility of the LINC-NIRVANA team at MPIA Heidelberg. It comprises the software for the real-time data acquisition from the accelerometers as well as the related telemetry interface and the vibration monitoring quick look tools. The basic design ideas, implementation details and special features are explained here.

Adaptive Management of Computing and Network Resources for Spacecraft Systems

NASA Technical Reports Server (NTRS)

Pfarr, Barbara; Welch, Lonnie R.; Detter, Ryan; Tjaden, Brett; Huh, Eui-Nam; Szczur, Martha R. (Technical Monitor)

2000-01-01

It is likely that NASA's future spacecraft systems will consist of distributed processes which will handle dynamically varying workloads in response to perceived scientific events, the spacecraft environment, spacecraft anomalies and user commands. Since all situations and possible uses of sensors cannot be anticipated during pre-deployment phases, an approach for dynamically adapting the allocation of distributed computational and communication resources is needed. To address this, we are evolving the DeSiDeRaTa adaptive resource management approach to enable reconfigurable ground and space information systems. The DeSiDeRaTa approach embodies a set of middleware mechanisms for adapting resource allocations, and a framework for reasoning about the real-time performance of distributed application systems. The framework and middleware will be extended to accommodate (1) the dynamic aspects of intra-constellation network topologies, and (2) the complete real-time path from the instrument to the user. We are developing a ground-based testbed that will enable NASA to perform early evaluation of adaptive resource management techniques without the expense of first deploying them in space. The benefits of the proposed effort are numerous, including the ability to use sensors in new ways not anticipated at design time; the production of information technology that ties the sensor web together; the accommodation of greater numbers of missions with fewer resources; and the opportunity to leverage the DeSiDeRaTa project's expertise, infrastructure and models for adaptive resource management for distributed real-time systems.

Klinefelter syndrome has increased brain responses to auditory stimuli and motor output, but not to visual stimuli or Stroop adaptation

PubMed Central

Wallentin, Mikkel; Skakkebæk, Anne; Bojesen, Anders; Fedder, Jens; Laurberg, Peter; Østergaard, John R.; Hertz, Jens Michael; Pedersen, Anders Degn; Gravholt, Claus Højbjerg

2016-01-01

Klinefelter syndrome (47, XXY) (KS) is a genetic syndrome characterized by the presence of an extra X chromosome and low level of testosterone, resulting in a number of neurocognitive abnormalities, yet little is known about brain function. This study investigated the fMRI-BOLD response from KS relative to a group of Controls to basic motor, perceptual, executive and adaptation tasks. Participants (N: KS = 49; Controls = 49) responded to whether the words “GREEN” or “RED” were displayed in green or red (incongruent versus congruent colors). One of the colors was presented three times as often as the other, making it possible to study both congruency and adaptation effects independently. Auditory stimuli saying “GREEN” or “RED” had the same distribution, making it possible to study effects of perceptual modality as well as Frequency effects across modalities. We found that KS had an increased response to motor output in primary motor cortex and an increased response to auditory stimuli in auditory cortices, but no difference in primary visual cortices. KS displayed a diminished response to written visual stimuli in secondary visual regions near the Visual Word Form Area, consistent with the widespread dyslexia in the group. No neural differences were found in inhibitory control (Stroop) or in adaptation to differences in stimulus frequencies. Across groups we found a strong positive correlation between age and BOLD response in the brain's motor network with no difference between groups. No effects of testosterone level or brain volume were found. In sum, the present findings suggest that auditory and motor systems in KS are selectively affected, perhaps as a compensatory strategy, and that this is not a systemic effect as it is not seen in the visual system. PMID:26958463

Klinefelter syndrome has increased brain responses to auditory stimuli and motor output, but not to visual stimuli or Stroop adaptation.

PubMed

Wallentin, Mikkel; Skakkebæk, Anne; Bojesen, Anders; Fedder, Jens; Laurberg, Peter; Østergaard, John R; Hertz, Jens Michael; Pedersen, Anders Degn; Gravholt, Claus Højbjerg

2016-01-01

Klinefelter syndrome (47, XXY) (KS) is a genetic syndrome characterized by the presence of an extra X chromosome and low level of testosterone, resulting in a number of neurocognitive abnormalities, yet little is known about brain function. This study investigated the fMRI-BOLD response from KS relative to a group of Controls to basic motor, perceptual, executive and adaptation tasks. Participants (N: KS = 49; Controls = 49) responded to whether the words "GREEN" or "RED" were displayed in green or red (incongruent versus congruent colors). One of the colors was presented three times as often as the other, making it possible to study both congruency and adaptation effects independently. Auditory stimuli saying "GREEN" or "RED" had the same distribution, making it possible to study effects of perceptual modality as well as Frequency effects across modalities. We found that KS had an increased response to motor output in primary motor cortex and an increased response to auditory stimuli in auditory cortices, but no difference in primary visual cortices. KS displayed a diminished response to written visual stimuli in secondary visual regions near the Visual Word Form Area, consistent with the widespread dyslexia in the group. No neural differences were found in inhibitory control (Stroop) or in adaptation to differences in stimulus frequencies. Across groups we found a strong positive correlation between age and BOLD response in the brain's motor network with no difference between groups. No effects of testosterone level or brain volume were found. In sum, the present findings suggest that auditory and motor systems in KS are selectively affected, perhaps as a compensatory strategy, and that this is not a systemic effect as it is not seen in the visual system.

Mini All-purpose Satellite Control Center (MASCC)

NASA Technical Reports Server (NTRS)

Zaouche, Gerard

1994-01-01

A new generation of Mini All-purpose Satellite Control Centers (MASCC) has been developed by CNES (F). They turn out to be easily adaptable to different kinds of satellites, both Low Earth Orbital or Geostationary. The features of MASCC allow both standard satellite control activities, and checking of passengers experiments hosted on a space platform. In the different environments in which it may be used, MASCC provides standard broadcasting of telemetry parameters on animated synoptics (curves, bar graphs, alphanumeric displays, ...), which turns out to be a very useful and ergonomic medium for operational teams or satellite specialists. Special care has been taken during the MASCC development about two points: - automation of all routine tasks, allowing automated operation, and limiting human commitment to system supervision and decision making, - software adaptability. To reach these two main objectives, the MASCC design provides:(1) a simple, robust and flexible hardware architecture, based on powerful distributed workstations; and (2) a table-driven software architecture, easily adapted to various operational needs. Satellite characteristics are described in a central Data Base. Hence, the processing of telemetry and commands is largely independent from the satellite itself. In order to validate these capabilities, the MASCC has been customized to several types of satellites and orbital platforms: (1) SPOT4, the French new generation of remote sensing satellites; (2) TELECOM2, the French geostationary TV and telecommunication satellite; and (3) MIR, the Russian orbital platform. MASCC development has been completed by the third quarter of 1993. This paper will provide first a description of the MASCC basic functions, of its hardware and software design. It will then detail the increased automation capability, along with the easy adaptation of the MASCC to new satellites with minimal software modifications.

Spacecraft Maneuvering at the Sun/Earth-Moon L2 Libration Point

NASA Astrophysics Data System (ADS)

Shahid, Kamran

Spacecraft formation flying in the vicinity of the Sun/Earth-Moon libration points offers many promising possibilities for space exploration. The concept of formation flying involves the distribution of the functionality of a single spacecraft among several smaller, cooperative spacecraft. The libration points are locations relative to two large orbiting bodies where a third body with relatively small mass can remain stationary relative to the two larger bodies. The most significant perturbation experienced by a spacecraft at the libration point is effect of solar radiation pressure. This thesis presents the development of nonlinear control techniques for maneuvering control at the Sun-Earth/Moon L2 libration point. A new thruster based formation control technique is presented. We also consider a leader/follower formation architecture, and examine the station keeping control of the leader spacecraft and the formation control of the follower spacecraft using solar radiation pressure. Reference trajectories of the leader spacecraft, halo and Lissajous orbits, are determined using a numerical technique in order to take into account all major gravitational perturbations. The nonlinear controllers are developed based on Lyapunov analysis, including non-adaptive and adaptive designs. Thruster based and solar radiation pressure based control laws for spacecraft maneuvering at the Sun-Earth/Moon libration point are developed. Higher order sliding mode control is utilized to address the non-affine structure of the solar sail control inputs. The reduced input solar radiation pressure problem is properly addressed as an underactuated control problem. The development of adaptive control for solar sail equipped spacecraft is an innovation and represents and advancement in solar sailing control technology. Controller performance is evaluated in a high fidelity ephemeris model to reflect a realistic simulated space environment. The numerical results demonstrate the effectiveness of the proposed control techniques for spacecraft maneuvering using solar radiation pressure at the L2 libration point. Stationkeeping accuracies of 50m and formation maintenance accuracies of less than 1m are possible using solar radiation pressure at a sub-L2 libration point. The benefits of these control techniques include increasing libration point mission lifetimes and doubling payload mass fractions as compared to conventional propulsion methods.

Genomic Trajectories to Desiccation Resistance: Convergence and Divergence Among Replicate Selected Drosophila Lines

PubMed Central

Griffin, Philippa C.; Hangartner, Sandra B.; Fournier-Level, Alexandre; Hoffmann, Ary A.

2017-01-01

Adaptation to environmental stress is critical for long-term species persistence. With climate change and other anthropogenic stressors compounding natural selective pressures, understanding the nature of adaptation is as important as ever in evolutionary biology. In particular, the number of alternative molecular trajectories available for an organism to reach the same adaptive phenotype remains poorly understood. Here, we investigate this issue in a set of replicated Drosophila melanogaster lines selected for increased desiccation resistance—a classical physiological trait that has been closely linked to Drosophila species distributions. We used pooled whole-genome sequencing (Pool-Seq) to compare the genetic basis of their selection responses, using a matching set of replicated control lines for characterizing laboratory (lab-)adaptation, as well as the original base population. The ratio of effective population size to census size was high over the 21 generations of the experiment at 0.52–0.88 for all selected and control lines. While selected SNPs in replicates of the same treatment (desiccation-selection or lab-adaptation) tended to change frequency in the same direction, suggesting some commonality in the selection response, candidate SNP and gene lists often differed among replicates. Three of the five desiccation-selection replicates showed significant overlap at the gene and network level. All five replicates showed enrichment for ovary-expressed genes, suggesting maternal effects on the selected trait. Divergence between pairs of replicate lines for desiccation-candidate SNPs was greater than between pairs of control lines. This difference also far exceeded the divergence between pairs of replicate lines for neutral SNPs. Overall, while there was overlap in the direction of allele frequency changes and the network and functional categories affected by desiccation selection, replicates showed unique responses at all levels, likely reflecting hitchhiking effects, and highlighting the challenges in identifying candidate genes from these types of experiments when traits are likely to be polygenic. PMID:28007884

Adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope

NASA Astrophysics Data System (ADS)

Ma, Haotong; Hu, Haojun; Xie, Wenke; Zhao, Haichuan; Xu, Xiaojun; Chen, Jinbao

2013-08-01

We demonstrate the adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope based on the stochastic parallel gradient descent (SPGD) algorithm and dual phase only liquid crystal spatial light modulators (LC-SLMs). Adaptive pre-compensation the wavefront of projected laser beam at the transmitter telescope is chosen to improve the power coupling efficiency. One phase only LC-SLM adaptively optimizes phase distribution of the projected laser beam and the other generates turbulence phase screen. The intensity distributions of the dark hollow beam after passing through the turbulent atmosphere with and without adaptive beam shaping are analyzed in detail. The influence of propagation distance and aperture size of the Cassegrain-telescope on coupling efficiency are investigated theoretically and experimentally. These studies show that the power coupling can be significantly improved by adaptive beam shaping. The technique can be used in optical communication, deep space optical communication and relay mirror.

An adaptive Cartesian control scheme for manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Temperature-stress resistance and tolerance along a latitudinal cline in North American Arabidopsis lyrata.

PubMed

Wos, Guillaume; Willi, Yvonne

2015-01-01

The study of latitudinal gradients can yield important insights into adaptation to temperature stress. Two strategies are available: resistance by limiting damage, or tolerance by reducing the fitness consequences of damage. Here we studied latitudinal variation in resistance and tolerance to frost and heat and tested the prediction of a trade-off between the two strategies and their costliness. We raised plants of replicate maternal seed families from eight populations of North American Arabidopsis lyrata collected along a latitudinal gradient in climate chambers and exposed them repeatedly to either frost or heat stress, while a set of control plants grew under standard conditions. When control plants reached maximum rosette size, leaf samples were exposed to frost and heat stress, and electrolyte leakage (PEL) was measured and treated as an estimate of resistance. Difference in maximum rosette size between stressed and control plants was used as an estimate of tolerance. Northern populations were more frost resistant, and less heat resistant and less heat tolerant, but-unexpectedly-they were also less frost tolerant. Negative genetic correlations between resistance and tolerance to the same and different thermal stress were generally not significant, indicating only weak trade-offs. However, tolerance to frost was consistently accompanied by small size under control conditions, which may explain the non-adaptive latitudinal pattern for frost tolerance. Our results suggest that adaptation to frost and heat is not constrained by trade-offs between them. But the cost of frost tolerance in terms of plant size reduction may be important for the limits of species distributions and climate niches.

Fundus-controlled two-color dark adaptometry with the Microperimeter MP1.

PubMed

Bowl, Wadim; Stieger, Knut; Lorenz, Birgit

2015-06-01

The aim of this study was to provide fundus-controlled two-color adaptometry with an existing device. A quick and easy approach extends the application possibilities of a commercial fundus-controlled perimeter. An external filter holder was placed in front the objective lens of the MP1 (Nidek, Italy) and fitted with filters to modify background, stimulus intensity, and color. Prior to dark adaptometry, the subject's visual sensitivity profile was measured for red and blue stimuli to determine whether rods or cones or both mediated the absolute threshold. After light adaptation, 20 healthy subjects were investigated with a pattern covering six spots at the posterior pole of the retina up to 45 min of dark adaptation. Thresholds were determined using a 200 ms red Goldmann IV and a blue Goldmann II stimulus. The pre-test sensitivity showed a typical distribution of values along the meridian, with high peripheral light increment sensitivity (LIS) and low central LIS for rods and the reverse for cones. After bleach, threshold recovery had a classic biphasic shape. The absolute threshold was reached after approximately 10 min for the red and 15 min for the blue stimulus. Two-color fundus-controlled adaptometry with a commercial MP1 without internal changes to the device provides a quick and easy examination of rod and cone function during dark adaptation at defined retinal loci of the posterior pole. This innovative method will be helpful to measure rod vs. cone function at known loci of the posterior pole in early stages of retinal degenerations.

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

NASA Astrophysics Data System (ADS)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Design of Low Complexity Model Reference Adaptive Controllers

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan

2012-01-01

Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

Leading toward value: the role of strategic human resource management in health system adaptability.

PubMed

Garman, Andrew N; Polavarapu, Nandakishor; Grady, Jane C; Canar, W Jeffrey

2013-01-01

Personnel costs typically account for 60% or more of total operating expenses in health systems, and as such become a necessary focus in most if not all substantive health reform adaptations. This study sought to assess whether strategic alignment of the human resource (HR) and learning functions was associated with greater adaptive capacity in U.S. health systems. Data were gathered using a survey that was distributed electronically to chief human resource officers from two U.S.-based associations. The survey included questions about organizational structure, strategic human resource management, strategic learning, and organizational response to health reform. Significant correlations were found between strategic alignment of HR and HR's involvement in responses related to cost control (r = 0.46, p < 0.01); quality improvement (r = 0.45, p < 0.01), and patient access (r = 0.39, p < 0.01). However, no significant relationships were found between strategic alignment of organizational learning and HR involvement with these responses. Results suggest that HR structure may affect an organization's capacity for adaptive response. Top-management teams in health systems should consider positioning HR as part of the core leadership team, with a reporting relationship that allows HR to maximally participate in formulating and implementing organizational adaptation.

An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size.

PubMed

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2014-09-01

Many papers have introduced adaptive clinical trial methods that allow modifications to the sample size based on interim estimates of treatment effect. There has been extensive commentary on type I error control and efficiency considerations, but little research on estimation after an adaptive hypothesis test. We evaluate the reliability and precision of different inferential procedures in the presence of an adaptive design with pre-specified rules for modifying the sampling plan. We extend group sequential orderings of the outcome space based on the stage at stopping, likelihood ratio statistic, and sample mean to the adaptive setting in order to compute median-unbiased point estimates, exact confidence intervals, and P-values uniformly distributed under the null hypothesis. The likelihood ratio ordering is found to average shorter confidence intervals and produce higher probabilities of P-values below important thresholds than alternative approaches. The bias adjusted mean demonstrates the lowest mean squared error among candidate point estimates. A conditional error-based approach in the literature has the benefit of being the only method that accommodates unplanned adaptations. We compare the performance of this and other methods in order to quantify the cost of failing to plan ahead in settings where adaptations could realistically be pre-specified at the design stage. We find the cost to be meaningful for all designs and treatment effects considered, and to be substantial for designs frequently proposed in the literature. © 2014, The International Biometric Society.

Unveiling adaptation using high-resolution lineage tracking

NASA Astrophysics Data System (ADS)

Blundell, Jamie; Levy, Sasha; Fisher, Daniel; Petrov, Dmitri; Sherlock, Gavin

2013-03-01

Human diseases such as cancer and microbial infections are adaptive processes inside the human body with enormous population sizes: between 106 -1012 cells. In spite of this our understanding of adaptation in large populations is limited. The key problem is the difficulty in identifying anything more than a handful of rare, large-effect beneficial mutations. The development and use of molecular barcodes allows us to uniquely tag hundreds of thousands of cells and enable us to track tens of thousands of adaptive mutations in large yeast populations. We use this system to test some of the key theories on which our understanding of adaptation in large populations is based. We (i) measure the fitness distribution in an evolving population at different times, (ii) identify when an appreciable fraction of clones in the population have at most a single adaptive mutation and isolate a large number of clones with independent single adaptive mutations, and (iii) use this clone collection to determine the distribution of fitness effects of single beneficial mutations.

Chemotaxonomy in some Mediterranean plants and implications for fossil biomarker records

NASA Astrophysics Data System (ADS)

Norström, Elin; Katrantsiotis, Christos; Smittenberg, Rienk H.; Kouli, Katerina

2017-12-01

The increasing utilization of n-alkanes as plant-derived paleo-environmental proxies calls for improved chemotaxonomic control of the modern flora in order to calibrate fossil sediment records to modern analogues. Several recent studies have investigated long-chain n-alkane concentrations and chain-length distributions in species from various vegetation biomes, but up to date, the Mediterranean flora is relatively unexplored in this respect. Here, we analyse the n-alkane concentrations and chain-length distributions in some of the most common species of the modern macchia and phrygana vegetation in south western Peloponnese, Greece. We show that the drought adapted phrygana herbs and shrubs, as well as some of the sclerophyll and gymnosperm macchia components, produce high concentrations of n-alkanes, on average more than double n-alkane production in local wetland reed vegetation. Furthermore, the chain-length distribution in the analysed plants is related to plant functionality, with longer chain lengths associated with higher drought adaptive capacities, probably as a response to long-term evolutionary processes in a moisture limited environment. Furthermore, species with relatively higher average chain lengths (ACL) showed more enriched carbon isotope composition in their tissues (δ13Cplant), suggesting a dual imprint from both physiological and biochemical drought adaptation. The findings have bearings on interpretation of fossil sedimentary biomarker records in the Mediterranean region, which is discussed in relation to a case study from Agios Floros fen, Messenian plain, Peloponnese. The 6000 year long n-alkane record from Agios Floros (ACL, δ13Cwax) is linked to the modern analogue and then evaluated through a comparison with other regional-wide as well as local climate and vegetation proxy-data. The high concentration of long chain n-alkanes in phrygana vegetation suggests a dominating imprint from this vegetation type in sedimentary archives from this ecotone.

Niche specialization of terrestrial archaeal ammonia oxidizers

PubMed Central

Gubry-Rangin, Cécile; Hai, Brigitte; Quince, Christopher; Engel, Marion; Thomson, Bruce C.; James, Phillip; Schloter, Michael; Griffiths, Robert I.; Prosser, James I.; Nicol, Graeme W.

2011-01-01

Soil pH is a major determinant of microbial ecosystem processes and potentially a major driver of evolution, adaptation, and diversity of ammonia oxidizers, which control soil nitrification. Archaea are major components of soil microbial communities and contribute significantly to ammonia oxidation in some soils. To determine whether pH drives evolutionary adaptation and community structure of soil archaeal ammonia oxidizers, sequences of amoA, a key functional gene of ammonia oxidation, were examined in soils at global, regional, and local scales. Globally distributed database sequences clustered into 18 well-supported phylogenetic lineages that dominated specific soil pH ranges classified as acidic (pH <5), acido-neutral (5≤ pH <7), or alkalinophilic (pH ≥7). To determine whether patterns were reproduced at regional and local scales, amoA gene fragments were amplified from DNA extracted from 47 soils in the United Kingdom (pH 3.5–8.7), including a pH-gradient formed by seven soils at a single site (pH 4.5–7.5). High-throughput sequencing and analysis of amoA gene fragments identified an additional, previously undiscovered phylogenetic lineage and revealed similar pH-associated distribution patterns at global, regional, and local scales, which were most evident for the five most abundant clusters. Archaeal amoA abundance and diversity increased with soil pH, which was the only physicochemical characteristic measured that significantly influenced community structure. These results suggest evolution based on specific adaptations to soil pH and niche specialization, resulting in a global distribution of archaeal lineages that have important consequences for soil ecosystem function and nitrogen cycling. PMID:22158986

Advanced Electric Distribution, Switching, and Conversion Technology for Power Control

NASA Technical Reports Server (NTRS)

Soltis, James V.

1998-01-01

The Electrical Power Control Unit currently under development by Sundstrand Aerospace for use on the Fluids Combustion Facility of the International Space Station is the precursor of modular power distribution and conversion concepts for future spacecraft and aircraft applications. This unit combines modular current-limiting flexible remote power controllers and paralleled power converters into one package. Each unit includes three 1-kW, current-limiting power converter modules designed for a variable-ratio load sharing capability. The flexible remote power controllers can be used in parallel to match load requirements and can be programmed for an initial ON or OFF state on powerup. The unit contains an integral cold plate. The modularity and hybridization of the Electrical Power Control Unit sets the course for future spacecraft electrical power systems, both large and small. In such systems, the basic hybridized converter and flexible remote power controller building blocks could be configured to match power distribution and conversion capabilities to load requirements. In addition, the flexible remote power controllers could be configured in assemblies to feed multiple individual loads and could be used in parallel to meet the specific current requirements of each of those loads. Ultimately, the Electrical Power Control Unit design concept could evolve to a common switch module hybrid, or family of hybrids, for both converter and switchgear applications. By assembling hybrids of a common current rating and voltage class in parallel, researchers could readily adapt these units for multiple applications. The Electrical Power Control Unit concept has the potential to be scaled to larger and smaller ratings for both small and large spacecraft and for aircraft where high-power density, remote power controllers or power converters are required and a common replacement part is desired for multiples of a base current rating.

Predicting and mapping malaria under climate change scenarios: the potential redistribution of malaria vectors in Africa.

PubMed

Tonnang, Henri E Z; Kangalawe, Richard Y M; Yanda, Pius Z

2010-04-23

Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa.

Using Response Times for Item Selection in Adaptive Testing

ERIC Educational Resources Information Center

van der Linden, Wim J.

2008-01-01

Response times on items can be used to improve item selection in adaptive testing provided that a probabilistic model for their distribution is available. In this research, the author used a hierarchical modeling framework with separate first-level models for the responses and response times and a second-level model for the distribution of the…

Predicting summer site occupancy for an invasive species, the common brushtail possum (Trichosurus vulpecula), in an urban environment.

PubMed

Adams, Amy L; Dickinson, Katharine J M; Robertson, Bruce C; van Heezik, Yolanda

2013-01-01

Invasive species are often favoured in fragmented, highly-modified, human-dominated landscapes such as urban areas. Because successful invasive urban adapters can occupy habitat that is quite different from that in their original range, effective management programmes for invasive species in urban areas require an understanding of distribution, habitat and resource requirements at a local scale that is tailored to the fine-scale heterogeneity typical of urban landscapes. The common brushtail possum (Trichosurus vulpecula) is one of New Zealand's most destructive invasive pest species. As brushtail possums traditionally occupy forest habitat, control in New Zealand has focussed on rural and forest habitats, and forest fragments in cities. However, as successful urban adapters, possums may be occupying a wider range of habitats. Here we use site occupancy methods to determine the distribution of brushtail possums across five distinguishable urban habitat types during summer, which is when possums have the greatest impacts on breeding birds. We collected data on possum presence/absence and habitat characteristics, including possible sources of supplementary food (fruit trees, vegetable gardens, compost heaps), and the availability of forest fragments from 150 survey locations. Predictive distribution models constructed using the programme PRESENCE revealed that while occupancy rates were highest in forest fragments, possums were still present across a large proportion of residential habitat with occupancy decreasing as housing density increased and green cover decreased. The presence of supplementary food sources was important in predicting possum occupancy, which may reflect the high nutritional value of these food types. Additionally, occupancy decreased as the proportion of forest fragment decreased, indicating the importance of forest fragments in determining possum distribution. Control operations to protect native birds from possum predation in cities should include well-vegetated residential areas; these modified habitats not only support possums but provide a source for reinvasion of fragments.

Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Kobezhicov, V.

2015-10-01

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

Real-time control of geometry and stiffness in adaptive structures

NASA Technical Reports Server (NTRS)

Ramesh, A. V.; Utku, S.; Wada, B. K.

1991-01-01

The basic theory is presented for the geometry, stiffness, and damping control of adaptive structures, with emphasis on adaptive truss structures. Necessary and sufficient conditions are given for stress-free geometry control in statically determinate and indeterminate adaptive discrete structures. Two criteria for selecting the controls are proposed, and their use in real-time control is illustrated by numerical simulation results. It is shown that the stiffness and damping control of adaptive truss structures for vibration suppression is possible by elongation and elongation rate dependent feedback forces from the active elements.

Optimal Control Modification for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

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. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Adaptive control in the presence of unmodeled dynamics. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Rohrs, C. E.

1982-01-01

Stability and robustness properties of a wide class of adaptive control algorithms in the presence of unmodeled dynamics and output disturbances were investigated. The class of adaptive algorithms considered are those commonly referred to as model reference adaptive control algorithms, self-tuning controllers, and dead beat adaptive controllers, developed for both continuous-time systems and discrete-time systems. A unified analytical approach was developed to examine the class of existing adaptive algorithms. It was discovered that all existing algorithms contain an infinite gain operator in the dynamic system that defines command reference errors and parameter errors; it is argued that such an infinite gain operator appears to be generic to all adaptive algorithms, whether they exhibit explicit or implicit parameter identification. It is concluded that none of the adaptive algorithms considered can be used with confidence in a practical control system design, because instability will set in with a high probability.

Closing the Certification Gaps in Adaptive Flight Control Software

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.

2008-01-01

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Anti-windup adaptive PID control design for a class of uncertain chaotic systems with input saturation.

PubMed

Tahoun, A H

2017-01-01

In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

SU-F-J-133: Adaptive Radiation Therapy with a Four-Dimensional Dose Calculation Algorithm That Optimizes Dose Distribution Considering Breathing Motion

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

Ali, I; Algan, O; Ahmad, S

Purpose: To model patient motion and produce four-dimensional (4D) optimized dose distributions that consider motion-artifacts in the dose calculation during the treatment planning process. Methods: An algorithm for dose calculation is developed where patient motion is considered in dose calculation at the stage of the treatment planning. First, optimal dose distributions are calculated for the stationary target volume where the dose distributions are optimized considering intensity-modulated radiation therapy (IMRT). Second, a convolution-kernel is produced from the best-fitting curve which matches the motion trajectory of the patient. Third, the motion kernel is deconvolved with the initial dose distribution optimized for themore » stationary target to produce a dose distribution that is optimized in four-dimensions. This algorithm is tested with measured doses using a mobile phantom that moves with controlled motion patterns. Results: A motion-optimized dose distribution is obtained from the initial dose distribution of the stationary target by deconvolution with the motion-kernel of the mobile target. This motion-optimized dose distribution is equivalent to that optimized for the stationary target using IMRT. The motion-optimized and measured dose distributions are tested with the gamma index with a passing rate of >95% considering 3% dose-difference and 3mm distance-to-agreement. If the dose delivery per beam takes place over several respiratory cycles, then the spread-out of the dose distributions is only dependent on the motion amplitude and not affected by motion frequency and phase. This algorithm is limited to motion amplitudes that are smaller than the length of the target along the direction of motion. Conclusion: An algorithm is developed to optimize dose in 4D. Besides IMRT that provides optimal dose coverage for a stationary target, it extends dose optimization to 4D considering target motion. This algorithm provides alternative to motion management techniques such as beam-gating or breath-holding and has potential applications in adaptive radiation therapy.« less

Safe-trajectory optimization and tracking control in ultra-close proximity to a failed satellite

NASA Astrophysics Data System (ADS)

Zhang, Jingrui; Chu, Xiaoyu; Zhang, Yao; Hu, Quan; Zhai, Guang; Li, Yanyan

2018-03-01

This paper presents a trajectory-optimization method for a chaser spacecraft operating in ultra-close proximity to a failed satellite. Based on the combination of active and passive trajectory protection, the constraints in the optimization framework are formulated for collision avoidance and successful docking in the presence of any thruster failure. The constraints are then handled by an adaptive Gauss pseudospectral method, in which the dynamic residuals are used as the metric to determine the distribution of collocation points. A finite-time feedback control is further employed in tracking the optimized trajectory. In particular, the stability and convergence of the controller are proved. Numerical results are given to demonstrate the effectiveness of the proposed methods.

Fault tolerant and lifetime control architecture for autonomous vehicles

NASA Astrophysics Data System (ADS)

Bogdanov, Alexander; Chen, Yi-Liang; Sundareswaran, Venkataraman; Altshuler, Thomas

2008-04-01

Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.

More pain, more gain: Blocking the opioid system boosts adaptive cognitive control.

PubMed

van Steenbergen, Henk; Weissman, Daniel H; Stein, Dan J; Malcolm-Smith, Susan; van Honk, Jack

2017-06-01

The ability to adaptively increase cognitive control in response to cognitive challenges is crucial for goal-directed behavior. Recent findings suggest that aversive arousal triggers adaptive increases of control, but the neurochemical mechanisms underlying these effects remain unclear. Given the known contributions of the opioid system to hedonic states, we investigated whether blocking this system increases adaptive control modulations. To do so, we conducted a double-blind, placebo-controlled psychopharmacological study (n=52 females) involving a Stroop-like task. Specifically, we assessed the effect of naltrexone, an opioid blocker most selective to the mu-opioid system, on two measures of adaptive control that are thought to depend differentially on aversive arousal: post-error slowing and conflict adaptation. Consistent with our hypothesis, relative to placebo, naltrexone increased post-error slowing without influencing conflict adaptation. This finding not only supports the view that aversive arousal triggers adaptive control but also reveals a novel role for the opioid system in modulating such effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neurovestibular adaptation in the utricular otolith in fish to hypergravity exposure and re-adaptation to 1G

NASA Astrophysics Data System (ADS)

Boyle, R.; Popova, Ye.; Varelas, J.; Mofrad, A.

The inner ear utricular organ senses the sum of inertial force due to head translation and head tilt relative to the gravitational vertical. A change in gravitational force has a profound effect on how an organism maintains equilibrium, and the neural response might involve the peripheral otolith receptors, the brain or both. If the influence of G leads to adaptation and subsequent re-adaptation processes in otolith function upon return to 1G, then this raises fundamental questions: does the transfer from 1G to 3G impart the opposite effects on changes of synaptic structure and gravitational sensitivity seen following G exposure? Do the effects accompanying transfer from the 3G to the 1G conditions resemble in part (as an analog) the transfer from 1G to the G? The use of well-controlled hyper-G experiments allows us to address these questions. Adult fish were placed in groups and exposed to 3G for 1, 2, 3, 4, 5, 8, 16, 24, and 32 days. Re-adaptation to 1G was studied in 3G exposure (4-and 16-day) following 1-8 day of recovery. Typically ∼60 afferents are well characterized in each fish. Directional sensitivity of each afferent defined as the vector with the magnitude measured in unit gain (imp/s/g) is determined. It allows us to consider the diagram of directional sensitivity of the whole macula. For quantitative estimates of the change of afferent sensitivity in hyper-G experiments two functions have been introduced: probability function (maximum sensitivity of each afferent is plotted as a percentage of population sensitivity whose values is less than the individual sensitivity) and the frequency function (or probability density function-PDF) of the population of afferents on the gain. These functions enable us to extract additional information about the details of evolution of gain-afferent distribution. Results to date show a biphasic pattern in reaction to 3G exposures: an initial sensitivity up-regulation (3-and 4-day) followed by a significant decrease after 16-day exposure. Return to control values following 16-day exposure is on the order of 8 days. On-Center Controls (228/s rotation about Earth vertical) at 4-and 16-days do not show any difference compare to ground controls. Utricular sensitivity is strongly regulated by altered gravity exposure, and transition from hypergravity to normal gravity seem to resemble the transfer from 1G to microgravity, and might be used as a ground-based model to study the neural response to transitions in gravity. Preliminary analysis of the afferent distributions changes caused by adaptation to hyper-G and re-adaptation to 1G that uses PDF allows us to assume that hyper-G and G cause the redistribution of afferents with different gains: those with higher gains become more activated (sensitive) than those with lower gains. The case of down-regulation corresponds to decrease of the PDF dispersion. It should be noted that efferent vestibular actions are not uniform on hair cells and afferents, and it is proposed that the changes brought on in otolith afferents by the transitions from one gravity state to another will be most prevalent and coincident in afferents strongly affected by efferent activation. Support Contributed By: NASA 03-OBPR-04

MODIS. Volume 1: MODIS level 1A software baseline requirements

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Fleig, Albert; Ardanuy, Philip; Goff, Thomas; Carpenter, Lloyd; Solomon, Carl; Storey, James

1994-01-01

This document describes the level 1A software requirements for the moderate resolution imaging spectroradiometer (MODIS) instrument. This includes internal and external requirements. Internal requirements include functional, operational, and data processing as well as performance, quality, safety, and security engineering requirements. External requirements include those imposed by data archive and distribution systems (DADS); scheduling, control, monitoring, and accounting (SCMA); product management (PM) system; MODIS log; and product generation system (PGS). Implementation constraints and requirements for adapting the software to the physical environment are also included.

Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2

NASA Technical Reports Server (NTRS)

Balas, Mark J.; Frost, Susan

2011-01-01

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

Adapting radiotherapy to hypoxic tumours

NASA Astrophysics Data System (ADS)

Malinen, Eirik; Søvik, Åste; Hristov, Dimitre; Bruland, Øyvind S.; Rune Olsen, Dag

2006-10-01

In the current work, the concepts of biologically adapted radiotherapy of hypoxic tumours in a framework encompassing functional tumour imaging, tumour control predictions, inverse treatment planning and intensity modulated radiotherapy (IMRT) were presented. Dynamic contrast enhanced magnetic resonance imaging (DCEMRI) of a spontaneous sarcoma in the nasal region of a dog was employed. The tracer concentration in the tumour was assumed related to the oxygen tension and compared to Eppendorf histograph measurements. Based on the pO2-related images derived from the MR analysis, the tumour was divided into four compartments by a segmentation procedure. DICOM structure sets for IMRT planning could be derived thereof. In order to display the possible advantages of non-uniform tumour doses, dose redistribution among the four tumour compartments was introduced. The dose redistribution was constrained by keeping the average dose to the tumour equal to a conventional target dose. The compartmental doses yielding optimum tumour control probability (TCP) were used as input in an inverse planning system, where the planning basis was the pO2-related tumour images from the MR analysis. Uniform (conventional) and non-uniform IMRT plans were scored both physically and biologically. The consequences of random and systematic errors in the compartmental images were evaluated. The normalized frequency distributions of the tracer concentration and the pO2 Eppendorf measurements were not significantly different. 28% of the tumour had, according to the MR analysis, pO2 values of less than 5 mm Hg. The optimum TCP following a non-uniform dose prescription was about four times higher than that following a uniform dose prescription. The non-uniform IMRT dose distribution resulting from the inverse planning gave a three times higher TCP than that of the uniform distribution. The TCP and the dose-based plan quality depended on IMRT parameters defined in the inverse planning procedure (fields and step-and-shoot intensity levels). Simulated random and systematic errors in the pO2-related images reduced the TCP for the non-uniform dose prescription. In conclusion, improved tumour control of hypoxic tumours by dose redistribution may be expected following hypoxia imaging, tumour control predictions, inverse treatment planning and IMRT.

Adaptive plasticity in vestibular influences on cardiovascular control

NASA Technical Reports Server (NTRS)

Yates, B. J.; Holmes, M. J.; Jian, B. J.

2000-01-01

Data collected in both human subjects and animal models indicate that the vestibular system influences the control of blood pressure. In animals, peripheral vestibular lesions diminish the capacity to rapidly and accurately make cardiovascular adjustments to changes in posture. Thus, one role of vestibulo-cardiovascular influences is to elicit changes in blood distribution in the body so that stable blood pressure is maintained during movement. However, deficits in correcting blood pressure following vestibular lesions diminish over time, and are less severe when non-labyrinthine sensory cues regarding body position in space are provided. These observations show that pathways that mediate vestibulo-sympathetic reflexes can be subject to plastic changes. This review considers the adaptive plasticity in cardiovascular responses elicited by the central vestibular system. Recent data indicate that the posterior cerebellar vermis may play an important role in adaptation of these responses, such that ablation of the posterior vermis impairs recovery of orthostatic tolerance following subsequent vestibular lesions. Furthermore, recent experiments suggest that non-labyrinthine inputs to the central vestibular system may be important in controlling blood pressure during movement, particularly following vestibular dysfunction. A number of sensory inputs appear to be integrated to produce cardiovascular adjustments during changes in posture. Although loss of any one of these inputs does not induce lability in blood pressure, it is likely that maximal blood pressure stability is achieved by the integration of a variety of sensory cues signaling body position in space.

Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.

2010-01-01

This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.

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

PubMed

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

2010-09-01

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

Adaptive Quadrature Detection for Multicarrier Continuous-Variable Quantum Key Distribution

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

2015-03-01

We propose the adaptive quadrature detection for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD scheme uses Gaussian subcarrier continuous variables for the information conveying and Gaussian sub-channels for the transmission. The proposed multicarrier detection scheme dynamically adapts to the sub-channel conditions using a corresponding statistics which is provided by our sophisticated sub-channel estimation procedure. The sub-channel estimation phase determines the transmittance coefficients of the sub-channels, which information are used further in the adaptive quadrature decoding process. We define the technique called subcarrier spreading to estimate the transmittance conditions of the sub-channels with a theoretical error-minimum in the presence of a Gaussian noise. We introduce the terms of single and collective adaptive quadrature detection. We also extend the results for a multiuser multicarrier CVQKD scenario. We prove the achievable error probabilities, the signal-to-noise ratios, and quantify the attributes of the framework. The adaptive detection scheme allows to utilize the extra resources of multicarrier CVQKD and to maximize the amount of transmittable information. This work was partially supported by the GOP-1.1.1-11-2012-0092 (Secure quantum key distribution between two units on optical fiber network) project sponsored by the EU and European Structural Fund, and by the COST Action MP1006.

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

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

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

A comparison of adaptive and adaptable automation under different levels of environmental stress.

PubMed

Sauer, Juergen; Kao, Chung-Shan; Wastell, David

2012-01-01

The effectiveness of different forms of adaptive and adaptable automation was examined under low- and high-stress conditions, in the form of different levels of noise. Thirty-six participants were assigned to one of the three types of variable automation (adaptive event-based, adaptive performance-based and adaptable serving as a control condition). Participants received 3 h of training on a simulation of a highly automated process control task and were subsequently tested during a 4-h session under noise exposure and quiet conditions. The results for performance suggested no clear benefits of one automation control mode over the other two. However, it emerged that participants under adaptable automation adopted a more active system management strategy and reported higher levels of self-confidence than in the two adaptive control modes. Furthermore, the results showed higher levels of perceived workload, fatigue and anxiety for performance-based adaptive automation control than the other two modes. This study compared two forms of adaptive automation (where the automated system flexibly allocates tasks between human and machine) with adaptable automation (where the human allocates the tasks). The adaptable mode showed marginal advantages. This is of relevance, given that this automation mode may also be easier to design.

Microwave power transmission system studies. Volume 2: Introduction, organization, environmental and spaceborne systems analyses

NASA Technical Reports Server (NTRS)

Maynard, O. E.; Brown, W. C.; Edwards, A.; Haley, J. T.; Meltz, G.; Howell, J. M.; Nathan, A.

1975-01-01

Introduction, organization, analyses, conclusions, and recommendations for each of the spaceborne subsystems are presented. Environmental effects - propagation analyses are presented with appendices covering radio wave diffraction by random ionospheric irregularities, self-focusing plasma instabilities and ohmic heating of the D-region. Analyses of dc to rf conversion subsystems and system considerations for both the amplitron and the klystron are included with appendices for the klystron covering cavity circuit calculations, output power of the solenoid-focused klystron, thermal control system, and confined flow focusing of a relativistic beam. The photovoltaic power source characteristics are discussed as they apply to interfacing with the power distribution flow paths, magnetic field interaction, dc to rf converter protection, power distribution including estimates for the power budget, weights, and costs. Analyses for the transmitting antenna consider the aperture illumination and size, with associated efficiencies and ground power distributions. Analyses of subarray types and dimensions, attitude error, flatness, phase error, subarray layout, frequency tolerance, attenuation, waveguide dimensional tolerances, mechanical including thermal considerations are included. Implications associated with transportation, assembly and packaging, attitude control and alignment are discussed. The phase front control subsystem, including both ground based pilot signal driven adaptive and ground command approaches with their associated phase errors, are analyzed.

The Global Epidemiological Situation of Schistosomiasis and New Approaches to Control and Research

PubMed Central

Engels, D.; Chitsulo, L.; Montresor, A.; Savioli, L.

2017-01-01

While the distribution of schistosomiasis has changed over the last fifty years and there have been successful control programmes, the number of people estimated to be infected or at risk of infection has not been reduced. Today, 85% of the number of infected people are estimated to be on the African continent where few control efforts are made. In terms of disease burden, there is therefore a growing discrepancy between sub-Saharan Africa and the rest of the world. WHO has now developed a dual strategy for the control of schistosomiasis: a strategy for morbidity control adapted to the public health context in high burden areas, and a strategy to consolidate control in areas where a low endemic level has been reached and elimination may be feasible. Related to this new vision, some research needs are pointed out. PMID:12020886

Synaptic Plasticity In Mammalian Gravity Sensors: Preliminary Results From SLS-2

NASA Technical Reports Server (NTRS)

Ross, M. D.; Hargens, Alan R. (Technical Monitor)

1996-01-01

Sensory conflict is the prevalent theoretical explanation for space adaptation syndrome. This ultrastructural study tests the hypothesis that peripheral gravity sensors (maculae) play a role. Results were obtained from the medial part of utricular maculae of adult rats exposed to microgravity for 14 days, and from controls. Means and statistical significance of synapse counts were calculated using SUPERANOVA(Trademark) and Scheffe's procedure for post-hoc comparisons. Preliminary findings are from 2 sets of 100 serial sections for each dataset. Synapses were doubled numerically in type II hair cells of utricular maculae collected on day 13 inflight compared to controls (11.4 +/- 7.1 vs. 5.3 +/- 3.8; p < 0.0001). Flight mean synaptic number declined rapidly postflight and became comparable to means of controls. Synapses also increased numerically in type I cells inflight (2.4 +/- 1.6 vs. 1.7 +/- 1.0; p < 0.0341). Postflight there were no significant differences in counts. Results concerning shifts in ribbon type and distribution are also largely replicating previous findings from flight studies. Results indicate that mammalian maculae are adaptive endorgans that retain the property of synaptic plasticity into the adult stage. Macular plasticity has clinical implications for balance disorders of peripheral origin.

Adaptive Suction and Blowing for Twin-Tail Buffet Control

NASA Technical Reports Server (NTRS)

Kandil, Osama A.; Yang, Zhi

1999-01-01

Adaptive active flow control for twin-tail buffet alleviation is investigated. The concept behind this technique is to place control ports on the tail outer and inner surfaces with flow suction or blowing applied through these ports in order to minimize the pressure difference across the tail. The suction or blowing volume flow rate from each port is proportional to the pressure difference across the tail at this location. A parametric study of the effects of the number and location of these ports on the buffet response is carried out. The computational model consists of a sharp-edged delta wing of aspect ratio one and swept-back flexible twin tail with taper ratio of 0.23. This complex multidisciplinary problem is solved sequentially using three sets of equations for the fluid flow, aeroelastic response and grid deformation, using a dynamic multi-block grid structure. The computational model is pitched at 30 deg angle of attack. The freestream Mach number and Reynolds number are 0.3 and 1.25 million, respectively. The model is investigated for the inboard position of the twin tails, which corresponds to a separation distance between the twin tails of 33% of the wing span. Comparison of the time history and power spectral density responses of the tails for various distributions of the control ports are presented and discussed.

Digital watermarking for secure and adaptive teleconferencing

NASA Astrophysics Data System (ADS)

Vorbrueggen, Jan C.; Thorwirth, Niels

2002-04-01

The EC-sponsored project ANDROID aims to develop a management system for secure active networks. Active network means allowing the network's customers to execute code (Java-based so-called proxylets) on parts of the network infrastructure. Secure means that the network operator nonetheless retains full control over the network and its resources, and that proxylets use ANDROID-developed facilities to provide secure applications. Management is based on policies and allows autonomous, distributed decisions and actions to be taken. Proxylets interface with the system via policies; among actions they can take is controlling execution of other proxylets or redirection of network traffic. Secure teleconferencing is used as the application to demonstrate the approach's advantages. A way to control a teleconference's data streams is to use digital watermarking of the video, audio and/or shared-whiteboard streams, providing an imperceptible and inseparable side channel that delivers information from originating or intermediate stations to downstream stations. Depending on the information carried by the watermark, these stations can take many different actions. Examples are forwarding decisions based on security classifications (possibly time-varying) at security boundaries, set-up and tear-down of virtual private networks, intelligent and adaptive transcoding, recorder or playback control (e.g., speaking off the record), copyright protection, and sender authentication.

The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

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

Barkana, Itzhak, E-mail: ibarkana@gmail.com

Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measuremore » of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.« less

Building Energy Modeling and Control Methods for Optimization and Renewables Integration

NASA Astrophysics Data System (ADS)

Burger, Eric M.

This dissertation presents techniques for the numerical modeling and control of building systems, with an emphasis on thermostatically controlled loads. The primary objective of this work is to address technical challenges related to the management of energy use in commercial and residential buildings. This work is motivated by the need to enhance the performance of building systems and by the potential for aggregated loads to perform load following and regulation ancillary services, thereby enabling the further adoption of intermittent renewable energy generation technologies. To increase the generalizability of the techniques, an emphasis is placed on recursive and adaptive methods which minimize the need for customization to specific buildings and applications. The techniques presented in this dissertation can be divided into two general categories: modeling and control. Modeling techniques encompass the processing of data streams from sensors and the training of numerical models. These models enable us to predict the energy use of a building and of sub-systems, such as a heating, ventilation, and air conditioning (HVAC) unit. Specifically, we first present an ensemble learning method for the short-term forecasting of total electricity demand in buildings. As the deployment of intermittent renewable energy resources continues to rise, the generation of accurate building-level electricity demand forecasts will be valuable to both grid operators and building energy management systems. Second, we present a recursive parameter estimation technique for identifying a thermostatically controlled load (TCL) model that is non-linear in the parameters. For TCLs to perform demand response services in real-time markets, online methods for parameter estimation are needed. Third, we develop a piecewise linear thermal model of a residential building and train the model using data collected from a custom-built thermostat. This model is capable of approximating unmodeled dynamics within a building by learning from sensor data. Control techniques encompass the application of optimal control theory, model predictive control, and convex distributed optimization to TCLs. First, we present the alternative control trajectory (ACT) representation, a novel method for the approximate optimization of non-convex discrete systems. This approach enables the optimal control of a population of non-convex agents using distributed convex optimization techniques. Second, we present a distributed convex optimization algorithm for the control of a TCL population. Experimental results demonstrate the application of this algorithm to the problem of renewable energy generation following. This dissertation contributes to the development of intelligent energy management systems for buildings by presenting a suite of novel and adaptable modeling and control techniques. Applications focus on optimizing the performance of building operations and on facilitating the integration of renewable energy resources.

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.

PubMed

Gao, Hui; Song, Yongduan; Wen, Changyun

In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.

Adaptive control of robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

Distributed Adaptive Control: Beyond Single-Instant, Discrete Variables

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Bieniawski, Stefan

2005-01-01

In extensive form noncooperative game theory, at each instant t, each agent i sets its state x, independently of the other agents, by sampling an associated distribution, q(sub i)(x(sub i)). The coupling between the agents arises in the joint evolution of those distributions. Distributed control problems can be cast the same way. In those problems the system designer sets aspects of the joint evolution of the distributions to try to optimize the goal for the overall system. Now information theory tells us what the separate q(sub i) of the agents are most likely to be if the system were to have a particular expected value of the objective function G(x(sub 1),x(sub 2), ...). So one can view the job of the system designer as speeding an iterative process. Each step of that process starts with a specified value of E(G), and the convergence of the q(sub i) to the most likely set of distributions consistent with that value. After this the target value for E(sub q)(G) is lowered, and then the process repeats. Previous work has elaborated many schemes for implementing this process when the underlying variables x(sub i) all have a finite number of possible values and G does not extend to multiple instants in time. That work also is based on a fixed mapping from agents to control devices, so that the the statistical independence of the agents' moves means independence of the device states. This paper also extends that work to relax all of these restrictions. This extends the applicability of that work to include continuous spaces and Reinforcement Learning. This paper also elaborates how some of that earlier work can be viewed as a first-principles justification of evolution-based search algorithms.

L1 Adaptive Control Law for Flexible Space Launch Vehicle and Proposed Plan for Flight Test Validation

NASA Technical Reports Server (NTRS)

Kharisov, Evgeny; Gregory, Irene M.; Cao, Chengyu; Hovakimyan, Naira

2008-01-01

This paper explores application of the L1 adaptive control architecture to a generic flexible Crew Launch Vehicle (CLV). Adaptive control has the potential to improve performance and enhance safety of space vehicles that often operate in very unforgiving and occasionally highly uncertain environments. NASA s development of the next generation space launch vehicles presents an opportunity for adaptive control to contribute to improved performance of this statically unstable vehicle with low damping and low bending frequency flexible dynamics. In this paper, we consider the L1 adaptive output feedback controller to control the low frequency structural modes and propose steps to validate the adaptive controller performance utilizing one of the experimental test flights for the CLV Ares-I Program.

Optimal Design of Piezoelectric Materials for Maximal Energy Harvesting

DTIC Science & Technology

2015-06-01

Wright. . 22 Figure 3.1 Energy harvesting bimorph cantilever with distributed piezoelectric transducers (gray) bonded to a substrate ( white ). Adapted...certain materials, such as zinc blende, sodium chlorate, boracite, tourmaline, cane sugar, Rochelle salt, and quartz, mechanical stresses induce...cantilever with distributed piezoelectric transducers (gray) bonded to a substrate ( white ). Adapted from Dutoit, Wardle and Kim [16]. 25 The general equations

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

DTIC Science & Technology

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

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

Yan Di; Liang Jian

Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect tomore » the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions: Adaptive treatment modification can be implemented including the expected treatment dose in the adaptive inverse planning optimization. The retrospective evaluation results demonstrate that utilizing the weekly adaptive inverse planning optimization, the dose distribution of h and n cancer treatment can be largely improved.« less

Data Sharing in DHT Based P2P Systems

NASA Astrophysics Data System (ADS)

Roncancio, Claudia; Del Pilar Villamil, María; Labbé, Cyril; Serrano-Alvarado, Patricia

The evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the “extreme” characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases for providing data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identifies important future research trends in data management in P2P DHT systems.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Adaptive hybrid control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Multipoint dynamically reconfigure adaptive distributed fiber optic acoustic emission sensor (FAESense) system for condition based maintenance

NASA Astrophysics Data System (ADS)

Mendoza, Edgar; Prohaska, John; Kempen, Connie; Esterkin, Yan; Sun, Sunjian; Krishnaswamy, Sridhar

2010-09-01

This paper describes preliminary results obtained under a Navy SBIR contract by Redondo Optics Inc. (ROI), in collaboration with Northwestern University towards the development and demonstration of a next generation, stand-alone and fully integrated, dynamically reconfigurable, adaptive fiber optic acoustic emission sensor (FAESense™) system for the in-situ unattended detection and localization of shock events, impact damage, cracks, voids, and delaminations in new and aging critical infrastructures found in ships, submarines, aircraft, and in next generation weapon systems. ROI's FAESense™ system is based on the integration of proven state-of-the-art technologies: 1) distributed array of in-line fiber Bragg gratings (FBGs) sensors sensitive to strain, vibration, and acoustic emissions, 2) adaptive spectral demodulation of FBG sensor dynamic signals using two-wave mixing interferometry on photorefractive semiconductors, and 3) integration of all the sensor system passive and active optoelectronic components within a 0.5-cm x 1-cm photonic integrated circuit microchip. The adaptive TWM demodulation methodology allows the measurement of dynamic high frequnency acoustic emission events, while compensating for passive quasi-static strain and temperature drifts. It features a compact, low power, environmentally robust 1-inch x 1-inch x 4-inch small form factor (SFF) package with no moving parts. The FAESense™ interrogation system is microprocessor-controlled using high data rate signal processing electronics for the FBG sensors calibration, temperature compensation and the detection and analysis of acoustic emission signals. Its miniaturized package, low power operation, state-of-the-art data communications, and low cost makes it a very attractive solution for a large number of applications in naval and maritime industries, aerospace, civil structures, the oil and chemical industry, and for homeland security applications.

Distributive routing and congestion control in wireless multihop ad hoc communication networks

NASA Astrophysics Data System (ADS)

Glauche, Ingmar; Krause, Wolfram; Sollacher, Rudolf; Greiner, Martin

2004-10-01

Due to their inherent complexity, engineered wireless multihop ad hoc communication networks represent a technological challenge. Having no mastering infrastructure the nodes have to selforganize themselves in such a way that for example network connectivity, good data traffic performance and robustness are guaranteed. In this contribution the focus is on routing and congestion control. First, random data traffic along shortest path routes is studied by simulations as well as theoretical modeling. Measures of congestion like end-to-end time delay and relaxation times are given. A scaling law of the average time delay with respect to network size is revealed and found to depend on the underlying network topology. In the second step, a distributive routing and congestion control is proposed. Each node locally propagates its routing cost estimates and information about its congestion state to its neighbors, which then update their respective cost estimates. This allows for a flexible adaptation of end-to-end routes to the overall congestion state of the network. Compared to shortest-path routing, the critical network load is significantly increased.

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

Prediction of thickness distribution of thermoformed multilayer ABS/PMMA sheets

NASA Astrophysics Data System (ADS)

Jobey, Caroline; Allanic, Nadine; Mousseau, Pierre; Deterre, Rémi

2016-10-01

In thermoforming, one of the main difficulties is to avoid the presence of weak thickness in the most deformed zones. After the heating stage, a bubbling step, leading to a first rate of deformation, is often used. In this work, we assess how the initial bubbling deformation can be controlled in order to obtain a homogeneous final thickness of the product. Experiments are performed on a multilayer sheet product. An industrial mould, corresponding to a casing of a non-licensed car, was adapted on a lab thermoformer. After presenting experimental thermal profiles of the multilayer sheets measured during the heating stage, a first geometric model is investigated to predict the thickness distribution. Numerical results are compared with measurements.

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

NASA Astrophysics Data System (ADS)

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; Safta, Cosmin; Munger, William

2017-09-01

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. The result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

Chronic alcohol exposure differentially affects activation of female locus coeruleus neurons and the subcellular distribution of corticotropin releasing factor receptors.

PubMed

Retson, T A; Reyes, B A; Van Bockstaele, E J

2015-01-02

Understanding the neurobiological bases for sex differences in alcohol dependence is needed to help guide the development of individualized therapies for alcohol abuse disorders. In the present study, alcohol-induced adaptations in (1) anxiety-like behavior, (2) patterns of c-Fos activation and (3) subcellular distribution of corticotropin releasing factor receptor in locus coeruleus (LC) neurons was investigated in male and female Sprague-Dawley rats that were chronically exposed to ethanol using a liquid diet. Results confirm and extend reports by others showing that chronic ethanol exposure produces an anxiogenic-like response in both male and female subjects. Ethanol-induced sex differences were observed with increased c-Fos expression in LC neurons of female ethanol-treated subjects compared to controls or male subjects. Results also reveal sex differences in the subcellular distribution of the CRFr in LC-noradrenergic neurons with female subjects exposed to ethanol exhibiting a higher frequency of plasmalemmal CRFrs. These adaptations have implications for LC neuronal activity and its neural targets across the sexes. Considering the important role of the LC in ethanol-induced activation of the hypothalamo-pituitary-adrenal (HPA) axis, the present results indicate important sex differences in feed-forward regulation of the HPA axis that may render alcohol dependent females more vulnerable to subsequent stress exposure. Copyright © 2014 Elsevier Inc. All rights reserved.

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

Goldsmith, Steven Y.

2004-06-22

An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.

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.

A new instantaneous torque control of PM synchronous motor for high-performance direct-drive applications

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

Chung, S.K.; Kim, H.S.; Kim, C.G.

1998-05-01

a new instantaneous torque-control strategy is presented for high-performance control of a permanent magnet (PM) synchronous motor. In order to deal with the torque pulsating problem of a PM synchronous motor in a low-speed region, new torque estimation and control techniques are proposed. The linkage flux of a PM synchronous motor is estimated using a model reference adaptive system technique, and the developed torque is instantaneously controlled by the proposed torque controller combining a variable structure control (VSC) with a space-vector pulse-width modulation (PWM). The proposed control provides the advantage of reducing the torque pulsation caused by the nonsinusoidal fluxmore » distribution. This control strategy is applied to the high-torque PM synchronous motor drive system for direct-drive applications and implemented by using a software of the digital signal processor (DSP) TMS320C30. The simulations and experiments are carried out for this system, and the results well demonstrate the effectiveness of the proposed control.« less

Patterns of Cross-Continental Variation in Tree Seed Mass in the Canadian Boreal Forest

PubMed Central

Liu, Jushan; Bai, Yuguang; Lamb, Eric G.; Simpson, Dale; Liu, Guofang; Wei, Yongsheng; Wang, Deli; McKenney, Daniel W.; Papadopol, Pia

2013-01-01

Seed mass is an adaptive trait affecting species distribution, population dynamics and community structure. In widely distributed species, variation in seed mass may reflect both genetic adaptation to local environments and adaptive phenotypic plasticity. Acknowledging the difficulty in separating these two aspects, we examined the causal relationships determining seed mass variation to better understand adaptability and/or plasticity of selected tree species to spatial/climatic variation. A total of 504, 481 and 454 seed collections of black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench) Voss) and jack pine (Pinus banksiana Lamb) across the Canadian Boreal Forest, respectively, were selected. Correlation analyses were used to determine how seed mass vary with latitude, longitude, and altitude. Structural Equation Modeling was used to examine how geographic and climatic variables influence seed mass. Climatic factors explained a large portion of the variation in seed mass (34, 14 and 29%, for black spruce, white spruce and jack pine, respectively), indicating species-specific adaptation to long term climate conditions. Higher annual mean temperature and winter precipitation caused greater seed mass in black spruce, but annual precipitation was the controlling factor for white spruce. The combination of factors such as growing season temperature and evapotranspiration, temperature seasonality and annual precipitation together determined seed mass of jack pine. Overall, sites with higher winter temperatures were correlated with larger seeds. Thus, long-term climatic conditions, at least in part, determined spatial variation in seed mass. Black spruce and Jack pine, species with relatively more specific habitat requirements and less plasticity, had more variation in seed mass explained by climate than did the more plastic species white spruce. As traits such as seed mass are related to seedling growth and survival, they potentially influence forest species composition in a changing climate and should be included in future modeling of vegetation shifts. PMID:23593392

Distributed estimation for adaptive sensor selection in wireless sensor networks

NASA Astrophysics Data System (ADS)

Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

2014-05-01

Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

Dynamic models of farmers adaptation to climate change (case of rice farmers in Cemoro Watershed, Central Java, Indonesia)

NASA Astrophysics Data System (ADS)

Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

2018-03-01

Farming activities are generally very sensitive to climate change variations. Global climate change will result in changes of patterns and distribution of rainfall. The impact of changing patterns and distribution of rainfall is the occurrence of early season shifts and periods of planting. Therefore, farmers need to adapt to the occurrence of climate change to avoid the decrease productivity on the farm land. This study aims to examine the impacts of climate change adaptation that farmers practiced on the farming productivity. The analysis is conducted dynamically using the Powersim 2.5. The result of analysis shows that the use of Planting Calendar and Integrated Crops Management technology can increase the rice productivity of certain area unity. Both technologies are the alternatives for farmers to adapt to climate change. Both farmers who adapt to climate change and do not adapt to climate change, experience an increase in rice production, time after time. However, farmers who adapt to climate change, increase their production faster than farmers who do not adapt to climate change. The use of the Planting Calendar and Integrated Crops Management strategy together as a farmers’ adaptation strategy is able to increase production compared to non-adaptive farmers.

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Adaptive Training of Manual Control: 1. Comparison of Three Adaptive Variables and Two Logic Schemes.

ERIC Educational Resources Information Center

Norman, D. A.; And Others

"Machine controlled adaptive training is a promising concept. In adaptive training the task presented to the trainee varies as a function of how well he performs. In machine controlled training, adaptive logic performs a function analogous to that performed by a skilled operator." This study looks at the ways in which gain-effective time…

Automatic Data Distribution for CFD Applications on Structured Grids

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Yan, Jerry

1999-01-01

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Flight Test Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

Monitoring the Performance of a Neuro-Adaptive Controller

NASA Technical Reports Server (NTRS)

Schumann, Johann; Gupta, Pramod

2004-01-01

Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

Learning to Control Actions: Transfer Effects following a Procedural Cognitive Control Computerized Training

PubMed Central

Shahar, Nitzan; Meiran, Nachshon

2015-01-01

Few studies have addressed action control training. In the current study, participants were trained over 19 days in an adaptive training task that demanded constant switching, maintenance and updating of novel action rules. Participants completed an executive functions battery before and after training that estimated processing speed, working memory updating, set-shifting, response inhibition and fluid intelligence. Participants in the training group showed greater improvement than a no-contact control group in processing speed, indicated by reduced reaction times in speeded classification tasks. No other systematic group differences were found across the different pre-post measurements. Ex-Gaussian fitting of the reaction-time distribution revealed that the reaction time reduction observed among trained participants was restricted to the right tail of the distribution, previously shown to be related to working memory. Furthermore, training effects were only found in classification tasks that required participants to maintain novel stimulus-response rules in mind, supporting the notion that the training improved working memory abilities. Training benefits were maintained in a 10-month follow-up, indicating relatively long-lasting effects. The authors conclude that training improved action-related working memory abilities. PMID:25799443

Adaptation in pronoun resolution: Evidence from Brazilian and European Portuguese.

PubMed

Fernandes, Eunice G; Luegi, Paula; Correa Soares, Eduardo; de la Fuente, Israel; Hemforth, Barbara

2018-04-26

Previous research accounting for pronoun resolution as a problem of probabilistic inference has not explored the phenomenon of adaptation, whereby the processor constantly tracks and adapts, rationally, to changes in a statistical environment. We investigate whether Brazilian (BP) and European Portuguese (EP) speakers adapt to variations in the probability of occurrence of ambiguous overt and null pronouns, in two experiments assessing resolution toward subject and object referents. For each variety (BP, EP), participants were faced with either the same number of null and overt pronouns (equal distribution), or with an environment with fewer overt (than null) pronouns (unequal distribution). We find that the preference for interpreting overt pronouns as referring back to an object referent (object-biased interpretation) is higher when there are fewer overt pronouns (i.e., in the unequal, relative to the equal distribution condition). This is especially the case for BP, a variety with higher prior frequency and smaller object-biased interpretation of overt pronouns, suggesting that participants adapted incrementally and integrated prior statistical knowledge with the knowledge obtained in the experiment. We hypothesize that comprehenders adapted rationally, with the goal of maintaining, across variations in pronoun probability, the likelihood of subject and object referents. Our findings unify insights from research in pronoun resolution and in adaptation, and add to previous studies in both topics: They provide evidence for the influence of pronoun probability in pronoun resolution, and for an adaptation process whereby the language processor not only tracks statistical information, but uses it to make interpretational inferences. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Stability and Performance Metrics for Adaptive Flight Control

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

2009-01-01

This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control

NASA Technical Reports Server (NTRS)

Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)

2015-01-01

Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

NASA Technical Reports Server (NTRS)

Gupta, Pramod; Loparo, Kenneth; Mackall, Dale; Schumann, Johann; Soares, Fola

2004-01-01

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Model and experiments to optimize co-adaptation in a simplified myoelectric control system.

PubMed

Couraud, M; Cattaert, D; Paclet, F; Oudeyer, P Y; de Rugy, A

2018-04-01

To compensate for a limb lost in an amputation, myoelectric prostheses use surface electromyography (EMG) from the remaining muscles to control the prosthesis. Despite considerable progress, myoelectric controls remain markedly different from the way we normally control movements, and require intense user adaptation. To overcome this, our goal is to explore concurrent machine co-adaptation techniques that are developed in the field of brain-machine interface, and that are beginning to be used in myoelectric controls. We combined a simplified myoelectric control with a perturbation for which human adaptation is well characterized and modeled, in order to explore co-adaptation settings in a principled manner. First, we reproduced results obtained in a classical visuomotor rotation paradigm in our simplified myoelectric context, where we rotate the muscle pulling vectors used to reconstruct wrist force from EMG. Then, a model of human adaptation in response to directional error was used to simulate various co-adaptation settings, where perturbations and machine co-adaptation are both applied on muscle pulling vectors. These simulations established that a relatively low gain of machine co-adaptation that minimizes final errors generates slow and incomplete adaptation, while higher gains increase adaptation rate but also errors by amplifying noise. After experimental verification on real subjects, we tested a variable gain that cumulates the advantages of both, and implemented it with directionally tuned neurons similar to those used to model human adaptation. This enables machine co-adaptation to locally improve myoelectric control, and to absorb more challenging perturbations. The simplified context used here enabled to explore co-adaptation settings in both simulations and experiments, and to raise important considerations such as the need for a variable gain encoded locally. The benefits and limits of extending this approach to more complex and functional myoelectric contexts are discussed.

Adaptive invasive species distribution models: A framework for modeling incipient invasions

USGS Publications Warehouse

Uden, Daniel R.; Allen, Craig R.; Angeler, David G.; Corral, Lucia; Fricke, Kent A.

2015-01-01

The utilization of species distribution model(s) (SDM) for approximating, explaining, and predicting changes in species’ geographic locations is increasingly promoted for proactive ecological management. Although frameworks for modeling non-invasive species distributions are relatively well developed, their counterparts for invasive species—which may not be at equilibrium within recipient environments and often exhibit rapid transformations—are lacking. Additionally, adaptive ecological management strategies address the causes and effects of biological invasions and other complex issues in social-ecological systems. We conducted a review of biological invasions, species distribution models, and adaptive practices in ecological management, and developed a framework for adaptive, niche-based, invasive species distribution model (iSDM) development and utilization. This iterative, 10-step framework promotes consistency and transparency in iSDM development, allows for changes in invasive drivers and filters, integrates mechanistic and correlative modeling techniques, balances the avoidance of type 1 and type 2 errors in predictions, encourages the linking of monitoring and management actions, and facilitates incremental improvements in models and management across space, time, and institutional boundaries. These improvements are useful for advancing coordinated invasive species modeling, management and monitoring from local scales to the regional, continental and global scales at which biological invasions occur and harm native ecosystems and economies, as well as for anticipating and responding to biological invasions under continuing global change.

Indirect learning control for nonlinear dynamical systems

NASA Technical Reports Server (NTRS)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Differences in collagen distribution of healthy and regenerated periodontium. Histomorphometric study in dogs.

PubMed

Souza, Sérgio L S; Macedo, Guilherme O; Silveira E Souza, Adriana M M; Taba, Mário; Novaes, Arthur B; Oliver, Constance; Jamur, Maria C; Correa, Vani M A

2013-10-01

Previous studies have shown that there is a relationship between periodontal disease and the distribution of collagen fibers. This study evaluated the distribution of collagen types I and III in regenerated bone and periodontal ligament, comparing them to the tissues near the regenerated area and to the healthy periodontium. In the third (P3) and fourth (P4) mandibular premolars of 5 healthy mongrel dogs, bilaterally, buccal class 2 furcation lesions were surgically created and chronified for 3 weeks. After that, full flaps were elevated and expanded polytetrafluoroethylene (e-PTFE) membranes were adapted, sutured and recovered by the flaps. Two weeks after surgery, two membranes on the same side were removed and the other membranes were removed four weeks after surgery. The dogs were euthanized at 12 weeks following placement of the e-PTFE membranes. P3 and P4 teeth as well as the second premolars (healthy control teeth) and their periodontal tissues were removed and histologically processed for Collagen Quantification (COLQ). The amount of type III collagen was higher in native bone compared to the regenerated area. For periodontal ligament, COLQ for type I collagen showed statistically significant differences (Tukeys's Multiple Comparison, p⟨0.05) between the regenerated groups and the control group. These differences were not found for type III COLQ. There are significant differences in collagen distribution among the regenerated, native and control tissues. Membrane removal 2 or 4 weeks postoperatively did not influence the collagen composition.