Science.gov

Sample records for adaptive control framework

  1. 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.

  2. Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

    SciTech Connect

    Williams, Rube B.

    2004-02-04

    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.

  3. A theoretical stochastic control framework for adapting radiotherapy to hypoxia

    NASA Astrophysics Data System (ADS)

    Saberian, Fatemeh; Ghate, Archis; Kim, Minsun

    2016-10-01

    Hypoxia, that is, insufficient oxygen partial pressure, is a known cause of reduced radiosensitivity in solid tumors, and especially in head-and-neck tumors. It is thus believed to adversely affect the outcome of fractionated radiotherapy. Oxygen partial pressure varies spatially and temporally over the treatment course and exhibits inter-patient and intra-tumor variation. Emerging advances in non-invasive functional imaging offer the future possibility of adapting radiotherapy plans to this uncertain spatiotemporal evolution of hypoxia over the treatment course. We study the potential benefits of such adaptive planning via a theoretical stochastic control framework using computer-simulated evolution of hypoxia on computer-generated test cases in head-and-neck cancer. The exact solution of the resulting control problem is computationally intractable. We develop an approximation algorithm, called certainty equivalent control, that calls for the solution of a sequence of convex programs over the treatment course; dose-volume constraints are handled using a simple constraint generation method. These convex programs are solved using an interior point algorithm with a logarithmic barrier via Newton’s method and backtracking line search. Convexity of various formulations in this paper is guaranteed by a sufficient condition on radiobiological tumor-response parameters. This condition is expected to hold for head-and-neck tumors and for other similarly responding tumors where the linear dose-response parameter is larger than the quadratic dose-response parameter. We perform numerical experiments on four test cases by using a first-order vector autoregressive process with exponential and rational-quadratic covariance functions from the spatiotemporal statistics literature to simulate the evolution of hypoxia. Our results suggest that dynamic planning could lead to a considerable improvement in the number of tumor cells remaining at the end of the treatment course

  4. XML in an Adaptive Framework for Instrument Control

    NASA Technical Reports Server (NTRS)

    Ames, Troy J.

    2004-01-01

    NASA Goddard Space Flight Center is developing an extensible framework for instrument command and control, known as Instrument Remote Control (IRC), that combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms.

  5. Classifying climate change adaptation frameworks

    NASA Astrophysics Data System (ADS)

    Armstrong, Jennifer

    2014-05-01

    Complex socio-ecological demographics are factors that must be considered when addressing adaptation to the potential effects of climate change. As such, a suite of deployable climate change adaptation frameworks is necessary. Multiple frameworks that are required to communicate the risks of climate change and facilitate adaptation. Three principal adaptation frameworks have emerged from the literature; Scenario - Led (SL), Vulnerability - Led (VL) and Decision - Centric (DC). This study aims to identify to what extent these adaptation frameworks; either, planned or deployed are used in a neighbourhood vulnerable to climate change. This work presents a criterion that may be used as a tool for identifying the hallmarks of adaptation frameworks and thus enabling categorisation of projects. The study focussed on the coastal zone surrounding the Sizewell nuclear power plant in Suffolk in the UK. An online survey was conducted identifying climate change adaptation projects operating in the study area. This inventory was analysed to identify the hallmarks of each adaptation project; Levels of dependency on climate model information, Metrics/units of analysis utilised, Level of demographic knowledge, Level of stakeholder engagement, Adaptation implementation strategies and Scale of adaptation implementation. The study found that climate change adaptation projects could be categorised, based on the hallmarks identified, in accordance with the published literature. As such, the criterion may be used to establish the matrix of adaptation frameworks present in a given area. A comprehensive summary of the nature of adaptation frameworks in operation in a locality provides a platform for further comparative analysis. Such analysis, enabled by the criterion, may aid the selection of appropriate frameworks enhancing the efficacy of climate change adaptation.

  6. Rebound: A Framework for Automated Component Adaptation

    NASA Technical Reports Server (NTRS)

    Penix, John; Lau, Sonie (Technical Monitor)

    1998-01-01

    The REBOUND adaptation framework organizes a collection of adaptation tactics in a way that they can be selected based on the components available for adaptation. Adaptation tactics are specified formally in terms of the relationship between the component to be adapted and the resulting adapted component. The tactic specifications are used as matching conditions for specification-based component retrieval, creating a 'retrieval for adaptation' scenario. The results of specification matching are used to guide component adaptation. Several examples illustrate how the framework guides component and tactic selection and how basic tactics are composed to form more powerful tactics.

  7. Adaptive Leadership Framework for Chronic Illness

    PubMed Central

    Anderson, Ruth A.; Bailey, Donald E.; Wu, Bei; Corazzini, Kirsten; McConnell, Eleanor S.; Thygeson, N. Marcus; Docherty, Sharron L.

    2015-01-01

    We propose the Adaptive Leadership Framework for Chronic Illness as a novel framework for conceptualizing, studying, and providing care. This framework is an application of the Adaptive Leadership Framework developed by Heifetz and colleagues for business. Our framework views health care as a complex adaptive system and addresses the intersection at which people with chronic illness interface with the care system. We shift focus from symptoms to symptoms and the challenges they pose for patients/families. We describe how providers and patients/families might collaborate to create shared meaning of symptoms and challenges to coproduce appropriate approaches to care. PMID:25647829

  8. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park.

    PubMed

    Martin, Julien; Fackler, Paul L; Nichols, James D; Runge, Michael C; McIntyre, Carol L; Lubow, Bruce L; McCluskie, Maggie C; Schmutz, Joel A

    2011-04-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.

  9. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

    USGS Publications Warehouse

    Martin, Julien; Fackler, Paul L.; Nichols, James D.; Runge, Michael C.; McIntyre, Carol L.; Lubow, Bruce L.; McCluskie, Maggie C.; Schmutz, Joel A.

    2011-01-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

  10. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park.

    PubMed

    Martin, Julien; Fackler, Paul L; Nichols, James D; Runge, Michael C; McIntyre, Carol L; Lubow, Bruce L; McCluskie, Maggie C; Schmutz, Joel A

    2011-04-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles. PMID:21342265

  11. An Adaptive Course Generation Framework

    ERIC Educational Resources Information Center

    Li, Frederick W. B.; Lau, Rynson W. H.; Dharmendran, Parthiban

    2010-01-01

    Existing adaptive e-learning methods are supported by student (user) profiling for capturing student characteristics, and course structuring for organizing learning materials according to topics and levels of difficulties. Adaptive courses are then generated by extracting materials from the course structure to match the criteria specified in the…

  12. Simple method for model reference adaptive control

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1989-01-01

    A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.

  13. 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.

  14. Instrument Remote Control Application Framework

    NASA Technical Reports Server (NTRS)

    Ames, Troy; Hostetter, Carl F.

    2006-01-01

    The Instrument Remote Control (IRC) architecture is a flexible, platform-independent application framework that is well suited for the control and monitoring of remote devices and sensors. IRC enables significant savings in development costs by utilizing extensible Markup Language (XML) descriptions to configure the framework for a specific application. The Instrument Markup Language (IML) is used to describe the commands used by an instrument, the data streams produced, the rules for formatting commands and parsing the data, and the method of communication. Often no custom code is needed to communicate with a new instrument or device. An IRC instance can advertise and publish a description about a device or subscribe to another device's description on a network. This simple capability of dynamically publishing and subscribing to interfaces enables a very flexible, self-adapting architecture for monitoring and control of complex instruments in diverse environments.

  15. Adaptive control with aerospace applications

    NASA Astrophysics Data System (ADS)

    Gadient, Ross

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

  16. 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.

  17. Adaptive Cruise Control (ACC)

    NASA Astrophysics Data System (ADS)

    Reif, Konrad

    Die adaptive Fahrgeschwindigkeitsregelung (ACC, Adaptive Cruise Control) ist eine Weiterentwicklung der konventionellen Fahrgeschwindigkeitsregelung, die eine konstante Fahrgeschwindigkeit einstellt. ACC überwacht mittels eines Radarsensors den Bereich vor dem Fahrzeug und passt die Geschwindigkeit den Gegebenheiten an. ACC reagiert auf langsamer vorausfahrende oder einscherende Fahrzeuge mit einer Reduzierung der Geschwindigkeit, sodass der vorgeschriebene Mindestabstand zum vorausfahrenden Fahrzeug nicht unterschritten wird. Hierzu greift ACC in Antrieb und Bremse ein. Sobald das vorausfahrende Fahrzeug beschleunigt oder die Spur verlässt, regelt ACC die Geschwindigkeit wieder auf die vorgegebene Sollgeschwindigkeit ein (Bild 1). ACC steht somit für eine Geschwindigkeitsregelung, die sich dem vorausfahrenden Verkehr anpasst.

  18. DANA: distributed numerical and adaptive modelling framework.

    PubMed

    Rougier, Nicolas P; Fix, Jérémy

    2012-01-01

    DANA is a python framework ( http://dana.loria.fr ) whose computational paradigm is grounded on the notion of a unit that is essentially a set of time dependent values varying under the influence of other units via adaptive weighted connections. The evolution of a unit's value are defined by a set of differential equations expressed in standard mathematical notation which greatly ease their definition. The units are organized into groups that form a model. Each unit can be connected to any other unit (including itself) using a weighted connection. The DANA framework offers a set of core objects needed to design and run such models. The modeler only has to define the equations of a unit as well as the equations governing the training of the connections. The simulation is completely transparent to the modeler and is handled by DANA. This allows DANA to be used for a wide range of numerical and distributed models as long as they fit the proposed framework (e.g. cellular automata, reaction-diffusion system, decentralized neural networks, recurrent neural networks, kernel-based image processing, etc.).

  19. An explanatory framework for adaptive personality differences.

    PubMed

    Wolf, Max; Weissing, Franz J

    2010-12-27

    We develop a conceptual framework for the understanding of animal personalities in terms of adaptive evolution. We focus on two basic questions. First, why do behavioural types exhibit limited behavioural plasticity, that is, behavioural correlations both across contexts and over time? Second, how can multiple behavioural types coexist within a single population? We emphasize differences in 'state' among individuals in combination with state-dependent behaviour. Some states are inherently stable and individual differences in such states can explain stable differences in suites of behaviour if it is adaptive to make behaviour in various contexts dependent on such states. Behavioural stability and cross-context correlations in behaviour are more difficult to explain if individual states are potentially more variable. In such cases stable personalities can result from state-dependent behaviour if state and behaviour mutually reinforce each other by feedback mechanisms. We discuss various evolutionary mechanisms for the maintenance of variation (in states and/or behaviour), including frequency-dependent selection, spatial variation with incomplete matching between habitat and phenotype, bet-hedging in a temporally fluctuating environment, and non-equilibrium dynamics. Although state differences are important, we also discuss how social conventions and social signalling can give rise to adaptive personality differences in the absence of state differences.

  20. Adaptive control for accelerators

    DOEpatents

    Eaton, Lawrie E.; Jachim, Stephen P.; Natter, Eckard F.

    1991-01-01

    An adaptive feedforward control loop is provided to stabilize accelerator beam loading of the radio frequency field in an accelerator cavity during successive pulses of the beam into the cavity. A digital signal processor enables an adaptive algorithm to generate a feedforward error correcting signal functionally determined by the feedback error obtained by a beam pulse loading the cavity after the previous correcting signal was applied to the cavity. Each cavity feedforward correcting signal is successively stored in the digital processor and modified by the feedback error resulting from its application to generate the next feedforward error correcting signal. A feedforward error correcting signal is generated by the digital processor in advance of the beam pulse to enable a composite correcting signal and the beam pulse to arrive concurrently at the cavity.

  1. Adaptive nonlinear flight control

    NASA Astrophysics Data System (ADS)

    Rysdyk, Rolf Theoduor

    1998-08-01

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

  2. Effects of incomplete adaption and disturbance in adaptive control

    NASA Technical Reports Server (NTRS)

    Lindorff, D. P.

    1972-01-01

    This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.

  3. An extended framework for adaptive playback-based video summarization

    NASA Astrophysics Data System (ADS)

    Peker, Kadir A.; Divakaran, Ajay

    2003-11-01

    In our previous work, we described an adaptive fast playback framework for video summarization where we changed the playback rate using the motion activity feature so as to maintain a constant "pace." This method provides an effective way of skimming through video, especially when the motion is not too complex and the background is mostly still, such as in surveillance video. In this paper, we present an extended summarization framework that, in addition to motion activity, uses semantic cues such as face or skin color appearance, speech and music detection, or other domain dependent semantically significant events to control the playback rate. The semantic features we use are computationally inexpensive and can be computed in compressed domain, yet are robust, reliable, and have a wide range of applicability across different content types. The presented framework also allows for adaptive summaries based on preference, for example, to include more dramatic vs. action elements, or vice versa. The user can switch at any time between the skimming and the normal playback modes. The continuity of the video is preserved, and complete omission of segments that may be important to the user is avoided by using adaptive fast playback instead of skipping over long segments. The rule-set and the input parameters can be further modified to fit a certain domain or application. Our framework can be used by itself, or as a subsequent presentation stage for a summary produced by any other summarization technique that relies on generating a sub-set of the content.

  4. Dynamic optimization and adaptive controller design

    NASA Astrophysics Data System (ADS)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  5. Evolving Systems and Adaptive Key Component Control

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  6. Adaptive change in corporate control practices.

    PubMed

    Alexander, J A

    1991-03-01

    Multidivisional organizations are not concerned with what structure to adopt but with how they should exercise control within the divisional form to achieve economic efficiencies. Using an information-processing framework, I examined control arrangements between the headquarters and operating divisions of such organizations and how managers adapted control practices to accommodate increasing environmental uncertainty. Also considered were the moderating effects of contextual attributes on such adaptive behavior. Analyses of panel data from 97 multihospital systems suggested that organizations generally practice selective decentralization under conditions of increasing uncertainty but that organizational age, dispersion, and initial control arrangements significantly moderate the direction and magnitude of such changes.

  7. 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.

  8. Proliferation as a framework for adaptive planning. Final report

    SciTech Connect

    Adkins, M.A.

    1993-02-22

    Throughout the forty years of the cold war, the military proficiently demonstrated planning, exercising, and employing against weapons of mass destruction -- specifically nuclear weapons. However, this planning has never targeted the spread of those weapons. The four stages of proliferation (supply, demand, indigenous, threatening) provide a framework for using the adaptive planning concept and identifying proactive military objectives. The existence of nuclear technology, command and control of the weapons of mass destruction, associated moral issues, or the value of assured deterrence between two nuclear weapon states are not addressed. Weapons of mass destruction are the example used to examine the stages of proliferation. Once planning for proliferation of weapons of 'mass destruction has been proven effective, this framework can be applied to other types of proliferants such as narcotic trafficking and transfer of conventional/high technology arms.

  9. Adaptive management of natural resources-framework and issues

    USGS Publications Warehouse

    Williams, B.K.

    2011-01-01

    Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management. ?? 2010.

  10. An Adaptive Sensor Mining Framework for Pervasive Computing Applications

    NASA Astrophysics Data System (ADS)

    Rashidi, Parisa; Cook, Diane J.

    Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

  11. A framework for evaluating wavelet based watermarking for scalable coded digital item adaptation attacks

    NASA Astrophysics Data System (ADS)

    Bhowmik, Deepayan; Abhayaratne, Charith

    2009-02-01

    A framework for evaluating wavelet based watermarking schemes against scalable coded visual media content adaptation attacks is presented. The framework, Watermark Evaluation Bench for Content Adaptation Modes (WEBCAM), aims to facilitate controlled evaluation of wavelet based watermarking schemes under MPEG-21 part-7 digital item adaptations (DIA). WEBCAM accommodates all major wavelet based watermarking in single generalised framework by considering a global parameter space, from which the optimum parameters for a specific algorithm may be chosen. WEBCAM considers the traversing of media content along various links and required content adaptations at various nodes of media supply chains. In this paper, the content adaptation is emulated by the JPEG2000 coded bit stream extraction for various spatial resolution and quality levels of the content. The proposed framework is beneficial not only as an evaluation tool but also as design tool for new wavelet based watermark algorithms by picking and mixing of available tools and finding the optimum design parameters.

  12. 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.

  13. Adaptive Control Of Remote Manipulator

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1989-01-01

    Robotic control system causes remote manipulator to follow closely reference trajectory in Cartesian reference frame in work space, without resort to computationally intensive mathematical model of robot dynamics and without knowledge of robot and load parameters. System, derived from linear multivariable theory, uses relatively simple feedforward and feedback controllers with model-reference adaptive control.

  14. Nonlinear and adaptive control

    NASA Technical Reports Server (NTRS)

    Athans, Michael

    1989-01-01

    The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies.

  15. Generating Adaptive Behaviour within a Memory-Prediction Framework

    PubMed Central

    Rawlinson, David; Kowadlo, Gideon

    2012-01-01

    The Memory-Prediction Framework (MPF) and its Hierarchical-Temporal Memory implementation (HTM) have been widely applied to unsupervised learning problems, for both classification and prediction. To date, there has been no attempt to incorporate MPF/HTM in reinforcement learning or other adaptive systems; that is, to use knowledge embodied within the hierarchy to control a system, or to generate behaviour for an agent. This problem is interesting because the human neocortex is believed to play a vital role in the generation of behaviour, and the MPF is a model of the human neocortex. We propose some simple and biologically-plausible enhancements to the Memory-Prediction Framework. These cause it to explore and interact with an external world, while trying to maximize a continuous, time-varying reward function. All behaviour is generated and controlled within the MPF hierarchy. The hierarchy develops from a random initial configuration by interaction with the world and reinforcement learning only. Among other demonstrations, we show that a 2-node hierarchy can learn to successfully play “rocks, paper, scissors” against a predictable opponent. PMID:22272231

  16. 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.

  17. Studying the clinical encounter with the Adaptive Leadership framework

    PubMed Central

    Bailey, Donald E; Docherty, Sharron L; Adams, Judith A; Carthron, Dana L; Corazzini, Kirsten; Day, Jennifer R; Neglia, Elizabeth; Thygeson, Marcus; Anderson, Ruth A

    2014-01-01

    In this paper we discuss the concept of leadership as a personal capability, not contingent on one's position in a hierarchy. This type of leadership allows us to reframe both the care-giving and organizational roles of nurses and other front-line clinical staff. Little research has been done to explore what leadership means at the point of care, particularly in reference to the relationship between health care practitioners and patients and their family caregivers. The Adaptive Leadership framework, based on complexity science theory, provides a useful lens to explore practitioners' leadership behaviors at the point of care. This framework proposes that there are two broad categories of challenges that patients face: technical and adaptive. Whereas technical challenges are addressed with technical solutions that are delivered by practitioners, adaptive challenges require the patient (or family member) to adjust to a new situation and to do the work of adapting, learning, and behavior change. Adaptive leadership is the work that practitioners do to mobilize and support patients to do the adaptive work. The purpose of this paper is to describe this framework and demonstrate its application to nursing research. We demonstrate the framework's utility with five exemplars of nursing research problems that range from the individual to the system levels. The framework has the potential to guide researchers to ask new questions and to gain new insights into how practitioners interact with patients at the point of care to increase the patient's ability to tackle challenging problems and improve their own health care outcomes. It is a potentially powerful framework for developing and testing a new generation of interventions to address complex issues by harnessing and learning about the adaptive capabilities of patients within their life contexts. PMID:24409083

  18. Studying the clinical encounter with the Adaptive Leadership framework.

    PubMed

    Bailey, Donald E; Docherty, Sharron L; Adams, Judith A; Carthron, Dana L; Corazzini, Kirsten; Day, Jennifer R; Neglia, Elizabeth; Thygeson, Marcus; Anderson, Ruth A

    2012-08-01

    In this paper we discuss the concept of leadership as a personal capability, not contingent on one's position in a hierarchy. This type of leadership allows us to reframe both the care-giving and organizational roles of nurses and other front-line clinical staff. Little research has been done to explore what leadership means at the point of care, particularly in reference to the relationship between health care practitioners and patients and their family caregivers. The Adaptive Leadership framework, based on complexity science theory, provides a useful lens to explore practitioners' leadership behaviors at the point of care. This framework proposes that there are two broad categories of challenges that patients face: technical and adaptive. Whereas technical challenges are addressed with technical solutions that are delivered by practitioners, adaptive challenges require the patient (or family member) to adjust to a new situation and to do the work of adapting, learning, and behavior change. Adaptive leadership is the work that practitioners do to mobilize and support patients to do the adaptive work. The purpose of this paper is to describe this framework and demonstrate its application to nursing research. We demonstrate the framework's utility with five exemplars of nursing research problems that range from the individual to the system levels. The framework has the potential to guide researchers to ask new questions and to gain new insights into how practitioners interact with patients at the point of care to increase the patient's ability to tackle challenging problems and improve their own health care outcomes. It is a potentially powerful framework for developing and testing a new generation of interventions to address complex issues by harnessing and learning about the adaptive capabilities of patients within their life contexts. PMID:24409083

  19. Criticality of Adaptive Control Dynamics

    NASA Astrophysics Data System (ADS)

    Patzelt, Felix; Pawelzik, Klaus

    2011-12-01

    We show, that stabilization of a dynamical system can annihilate observable information about its structure. This mechanism induces critical points as attractors in locally adaptive control. It also reveals, that previously reported criticality in simple controllers is caused by adaptation and not by other controller details. We apply these results to a real-system example: human balancing behavior. A model of predictive adaptive closed-loop control subject to some realistic constraints is introduced and shown to reproduce experimental observations in unprecedented detail. Our results suggests, that observed error distributions in between the Lévy and Gaussian regimes may reflect a nearly optimal compromise between the elimination of random local trends and rare large errors.

  20. Adaptive Control For Flexible Structures

    NASA Technical Reports Server (NTRS)

    Bayard, David S.; Ih, Che-Hang Charles; Wang, Shyh Jong

    1988-01-01

    Paper discusses ways to cope with measurement noise in adaptive control system for large, flexible structure in outer space. System generates control signals for torque and thrust actuators to turn all or parts of structure to desired orientations while suppressing torsional and other vibrations. Main result of paper is general theory for introduction of filters to suppress measurement noise while preserving stability.

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

    PubMed

    Fei, Juntao; Zhou, Jian

    2012-12-01

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

  2. Framework for Adaptable Operating and Runtime Systems: Final Project Report

    SciTech Connect

    Patrick G. Bridges

    2012-02-01

    In this grant, we examined a wide range of techniques for constructing high-performance con gurable system software for HPC systems and its application to DOE-relevant problems. Overall, research and development on this project focused in three specifc areas: (1) software frameworks for constructing and deploying con gurable system software, (2) applcation of these frameworks to HPC-oriented adaptable networking software, (3) performance analysis of HPC system software to understand opportunities for performance optimization.

  3. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

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

  4. 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.

  5. A framework for constructing adaptive and reconfigurable systems

    SciTech Connect

    Poirot, Pierre-Etienne; Nogiec, Jerzy; Ren, Shangping; /IIT, Chicago

    2007-05-01

    This paper presents a software approach to augmenting existing real-time systems with self-adaptation capabilities. In this approach, based on the control loop paradigm commonly used in industrial control, self-adaptation is decomposed into observing system events, inferring necessary changes based on a system's functional model, and activating appropriate adaptation procedures. The solution adopts an architectural decomposition that emphasizes independence and separation of concerns. It encapsulates observation, modeling and correction into separate modules to allow for easier customization of the adaptive behavior and flexibility in selecting implementation technologies.

  6. An adaptive online learning framework for practical breast cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Chu, Tianshu; Wang, Jie; Chen, Jiayu

    2016-03-01

    This paper presents an adaptive online learning (OL) framework for supporting clinical breast cancer (BC) diagnosis. Unlike traditional data mining, which trains a particular model from a fixed set of medical data, our framework offers robust OL models that can be updated adaptively according to new data sequences and newly discovered features. As a result, our framework can naturally learn to perform BC diagnosis using experts' opinions on sequential patient cases with cumulative clinical measurements. The framework integrates both supervised learning (SL) models for BC risk assessment and reinforcement learning (RL) models for decision-making of clinical measurements. In other words, online SL and RL interact with one another, and under a doctor's supervision, push the patient's diagnosis further. Furthermore, our framework can quickly update relevant model parameters based on current diagnosis information during the training process. Additionally, it can build flexible fitted models by integrating different model structures and plugging in the corresponding parameters during the prediction (or decision-making) process. Even when the feature space is extended, it can initialize the corresponding parameters and extend the existing model structure without loss of the cumulative knowledge. We evaluate the OL framework on real datasets from BCSC and WBC, and demonstrate that our SL models achieve accurate BC risk assessment from sequential data and incremental features. We also verify that the well-trained RL models provide promising measurement suggestions.

  7. Applying statistical process control to the adaptive rate control problem

    NASA Astrophysics Data System (ADS)

    Manohar, Nelson R.; Willebeek-LeMair, Marc H.; Prakash, Atul

    1997-12-01

    Due to the heterogeneity and shared resource nature of today's computer network environments, the end-to-end delivery of multimedia requires adaptive mechanisms to be effective. We present a framework for the adaptive streaming of heterogeneous media. We introduce the application of online statistical process control (SPC) to the problem of dynamic rate control. In SPC, the goal is to establish (and preserve) a state of statistical quality control (i.e., controlled variability around a target mean) over a process. We consider the end-to-end streaming of multimedia content over the internet as the process to be controlled. First, at each client, we measure process performance and apply statistical quality control (SQC) with respect to application-level requirements. Then, we guide an adaptive rate control (ARC) problem at the server based on the statistical significance of trends and departures on these measurements. We show this scheme facilitates handling of heterogeneous media. Last, because SPC is designed to monitor long-term process performance, we show that our online SPC scheme could be used to adapt to various degrees of long-term (network) variability (i.e., statistically significant process shifts as opposed to short-term random fluctuations). We develop several examples and analyze its statistical behavior and guarantees.

  8. Adaptable state based control system

    NASA Technical Reports Server (NTRS)

    Rasmussen, Robert D. (Inventor); Dvorak, Daniel L. (Inventor); Gostelow, Kim P. (Inventor); Starbird, Thomas W. (Inventor); Gat, Erann (Inventor); Chien, Steve Ankuo (Inventor); Keller, Robert M. (Inventor)

    2004-01-01

    An autonomous controller, comprised of a state knowledge manager, a control executor, hardware proxies and a statistical estimator collaborates with a goal elaborator, with which it shares common models of the behavior of the system and the controller. The elaborator uses the common models to generate from temporally indeterminate sets of goals, executable goals to be executed by the controller. The controller may be updated to operate in a different system or environment than that for which it was originally designed by the replacement of shared statistical models and by the instantiation of a new set of state variable objects derived from a state variable class. The adaptation of the controller does not require substantial modification of the goal elaborator for its application to the new system or environment.

  9. Method For Model-Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1990-01-01

    Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.

  10. Adaptive controller for hyperthermia robot

    SciTech Connect

    Kress, R.L.

    1997-03-01

    This paper describes the development of an adaptive computer control routine for a robotically, deployed focused, ultrasonic hyperthermia cancer treatment system. The control algorithm developed herein uses physiological models of a tumor and the surrounding healthy tissue regions and transient temperature data to estimate the treatment region`s blood perfusion. This estimate is used to vary the specific power profile of a scanned, focused ultrasonic transducer to achieve a temperature distribution as close as possible to an optimal temperature distribution. The controller is evaluated using simulations of diseased tissue and using limited experiments on a scanned, focused ultrasonic treatment system that employs a 5-Degree-of-Freedom (D.O.F.) robot to scan the treatment transducers over a simulated patient. Results of the simulations and experiments indicate that the adaptive control routine improves the temperature distribution over standard classical control algorithms if good (although not exact) knowledge of the treated region is available. Although developed with a scanned, focused ultrasonic robotic treatment system in mind, the control algorithm is applicable to any system with the capability to vary specific power as a function of volume and having an unknown distributed energy sink proportional to temperature elevation (e.g., other robotically deployed hyperthermia treatment methods using different heating modalities).

  11. A Framework for Context-Aware Adaptation in Public Displays

    NASA Astrophysics Data System (ADS)

    Cardoso, Jorge C. S.; José, Rui

    Several approaches for context-aware public display systems exist but none has been able to bridge the gap between the myriad of possible interactive features of a display and adaptation rules for its content. In this paper, we propose a framework of digital footprints generated by the interaction with public displays that can be used as a means to dynamically characterise a place. We describe these footprints, how they can be generated and how they can be used by context-aware display systems to adapt to the social environment of a place.

  12. Effects of incomplete adaptation and disturbance in adaptive control.

    NASA Technical Reports Server (NTRS)

    Lindorff, D. P.

    1972-01-01

    In this paper consideration is given to the effects of disturbance and incomplete parameter adaptation on the performance of adaptive control systems in which Liapunov theory is used in deriving the control law. A design equation for the bounded error is derived. It is further shown that parameters in the adaptive controller may not converge in the presence of disturbance unless the input signal has a rich enough frequency constant. Design examples are presented.

  13. Keck adaptive optics: control subsystem

    SciTech Connect

    Brase, J.M.; An, J.; Avicola, K.

    1996-03-08

    Adaptive optics on the Keck 10 meter telescope will provide an unprecedented level of capability in high resolution ground based astronomical imaging. The system is designed to provide near diffraction limited imaging performance with Strehl {gt} 0.3 n median Keck seeing of r0 = 25 cm, T =10 msec at 500 nm wavelength. The system will be equipped with a 20 watt sodium laser guide star to provide nearly full sky coverage. The wavefront control subsystem is responsible for wavefront sensing and the control of the tip-tilt and deformable mirrors which actively correct atmospheric turbulence. The spatial sampling interval for the wavefront sensor and deformable mirror is de=0.56 m which gives us 349 actuators and 244 subapertures. This paper summarizes the wavefront control system and discusses particular issues in designing a wavefront controller for the Keck telescope.

  14. Internal models in sensorimotor integration: perspectives from adaptive control theory.

    PubMed

    Tin, Chung; Poon, Chi-Sang

    2005-09-01

    Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems-such as sensorimotor prediction or the resolution of vestibular sensory ambiguity-is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.

  15. Adaptive Force Control in Compliant Motion

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1994-01-01

    This paper addresses the problem of controlling a manipulator in compliant motion while in contact with an environment having an unknown stiffness. Two classes of solutions are discussed: adaptive admittance control and adaptive compliance control. In both admittance and compliance control schemes, compensator adaptation is used to ensure a stable and uniform system performance.

  16. 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.

  17. Adaptive framework for uncertainty analysis in electromagnetic field measurements.

    PubMed

    Prieto, Javier; Alonso, Alonso A; de la Rosa, Ramón; Carrera, Albano

    2015-04-01

    Misinterpretation of uncertainty in the measurement of the electromagnetic field (EMF) strength may lead to an underestimation of exposure risk or an overestimation of required measurements. The Guide to the Expression of Uncertainty in Measurement (GUM) has internationally been adopted as a de facto standard for uncertainty assessment. However, analyses under such an approach commonly assume unrealistic static models or neglect relevant prior information, resulting in non-robust uncertainties. This study proposes a principled and systematic framework for uncertainty analysis that fuses information from current measurements and prior knowledge. Such a framework dynamically adapts to data by exploiting a likelihood function based on kernel mixtures and incorporates flexible choices of prior information by applying importance sampling. The validity of the proposed techniques is assessed from measurements performed with a broadband radiation meter and an isotropic field probe. The developed framework significantly outperforms GUM approach, achieving a reduction of 28% in measurement uncertainty.

  18. An advanced intelligent control system framework

    NASA Technical Reports Server (NTRS)

    Nemeth, ED; Anderson, Ronald R.; Maram, Jon; Norman, Arnie; Merrill, Walt

    1992-01-01

    A reusable rocket-engine intelligent control system (RREICS) framework was developed to a define a control framework for rocket-engine systems that reduces the required engine maintenance, extends the useful operating life, and maximizes the probability of mission success. The RREICS framework defines a controller that handles a rocket engine cluster as a single system rather than as a collection of individual engines. This enables the controller to alter individual engine operations in response to engine performance or integrity degradations while maintaining the propulsion subsystem external parameters at the levels required for mission success. A simplified model of a three engine cluster and the associated propulsion subsystem controller is also described.

  19. 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.

  20. A New Adaptive Framework for Collaborative Filtering Prediction.

    PubMed

    Almosallam, Ibrahim A; Shang, Yi

    2008-06-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix's system.

  1. A New Adaptive Framework for Collaborative Filtering Prediction

    PubMed Central

    Almosallam, Ibrahim A.; Shang, Yi

    2010-01-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix’s system. PMID:21572924

  2. 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.

  3. A Framework for the Development of Computerized Adaptive Tests

    ERIC Educational Resources Information Center

    Thompson, Nathan A.; Weiss, David J.

    2011-01-01

    A substantial amount of research has been conducted over the past 40 years on technical aspects of computerized adaptive testing (CAT), such as item selection algorithms, item exposure controls, and termination criteria. However, there is little literature providing practical guidance on the development of a CAT. This paper seeks to collate some…

  4. A general framework for adaptive processing of data structures.

    PubMed

    Frasconi, P; Gori, M; Sperduti, A

    1998-01-01

    A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to relatively poor structures, like arrays or sequences. The framework described in this paper is an attempt to unify adaptive models like artificial neural nets and belief nets for the problem of processing structured information. In particular, relations between data variables are expressed by directed acyclic graphs, where both numerical and categorical values coexist. The general framework proposed in this paper can be regarded as an extension of both recurrent neural networks and hidden Markov models to the case of acyclic graphs. In particular we study the supervised learning problem as the problem of learning transductions from an input structured space to an output structured space, where transductions are assumed to admit a recursive hidden statespace representation. We introduce a graphical formalism for representing this class of adaptive transductions by means of recursive networks, i.e., cyclic graphs where nodes are labeled by variables and edges are labeled by generalized delay elements. This representation makes it possible to incorporate the symbolic and subsymbolic nature of data. Structures are processed by unfolding the recursive network into an acyclic graph called encoding network. In so doing, inference and learning algorithms can be easily inherited from the corresponding algorithms for artificial neural networks or probabilistic graphical model.

  5. Statistical Physics for Adaptive Distributed Control

    NASA Technical Reports Server (NTRS)

    Wolpert, David H.

    2005-01-01

    A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.

  6. 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.

  7. Adaptive, predictive controller for optimal process control

    SciTech Connect

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  8. A framework for adaptive routing in multicomputer networks

    SciTech Connect

    Ngai, J.Y.K.

    1989-01-01

    Message-passing concurrent computers, also known as multicomputers, such as the Caltech Cosmic Cube and its commercial descendants, consist of many computing nodes that interact with each other by sending and receiving messages over communication channels between the nodes. The communication networks of the second-generation machines, such as the Symult Series 2010 and the Intel iPSC2, employ an oblivious wormhole-routing technique that guarantees deadlock freedom. The network performance of this highly evolved oblivious technique has reached a limit of being capable of delivering, under random traffic, a stable maximum sustained throughput of {approx}45 to 50% of the limit set by the network bisection bandwidth, while maintaining acceptable network latency. This thesis examines the possibility of performing adaptive routing as an approach to further improving upon the performance and reliability of these networks. In an adaptive multipath routing scheme, message trajectories are no longer deterministic, but are continuously perturbed by local message loading. Message packets will tend to follow their shortest-distance routes to destinations in normal traffic loading, but can be detoured to longer but less-loaded routes as local congestion occurs. Our study of the proposed adaptive routing framework is organized around four major areas of interest: establishing the theoretical feasibility, investigating the performance behavior, exploring the potential reliability enhancement, and examining the major implementation issues.

  9. Integrated Framework for an Urban Climate Adaptation Tool

    NASA Astrophysics Data System (ADS)

    Omitaomu, O.; Parish, E. S.; Nugent, P.; Mei, R.; Sylvester, L.; Ernst, K.; Absar, M.

    2015-12-01

    Cities have an opportunity to become more resilient to future climate change through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. In this paper, we present some of the methods that drive each of the modules and demo some of the capabilities available to-date using the City of Knoxville in Tennessee as a case study.

  10. Research in digital adaptive flight controllers

    NASA Technical Reports Server (NTRS)

    Kaufman, H.

    1976-01-01

    A design study of adaptive control logic suitable for implementation in modern airborne digital flight computers was conducted. Both explicit controllers which directly utilize parameter identification and implicit controllers which do not require identification were considered. Extensive analytical and simulation efforts resulted in the recommendation of two explicit digital adaptive flight controllers. Interface weighted least squares estimation procedures with control logic were developed using either optimal regulator theory or with control logic based upon single stage performance indices.

  11. 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.

  12. Adaptive control: Myths and realities

    NASA Technical Reports Server (NTRS)

    Athans, M.; Valavani, L.

    1984-01-01

    It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.

  13. 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.

  14. A Multiscale Computational Framework to Understand Vascular Adaptation

    PubMed Central

    Garbey, Marc; Rahman, Mahbubur; Berceli, Scott A.

    2015-01-01

    The failure rate for vascular interventions (vein bypass grafting, arterial angioplasty/stenting) remains unacceptably high. Over the past two decades, researchers have applied a wide variety of approaches to investigate the primary failure mechanisms, neointimal hyperplasia and aberrant remodeling of the wall, in an effort to identify novel therapeutic strategies. Despite incremental progress, specific cause/effect linkages among the primary drivers of the pathology, (hemodynamic factors, inflammatory biochemical mediators, cellular effectors) and vascular occlusive phenotype remain lacking. We propose a multiscale computational framework of vascular adaptation to develop a bridge between theory and experimental observation and to provide a method for the systematic testing of relevant clinical hypotheses. Cornerstone to our model is a feedback mechanism between environmental conditions and dynamic tissue plasticity described at the cellular level with an agent based model. Our implementation (i) is modular, (ii) starts from basic mechano-biology principle at the cell level and (iii) facilitates the agile development of the model. PMID:25977733

  15. 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.

  16. Modular and Adaptive Control of Sound Processing

    NASA Astrophysics Data System (ADS)

    van Nort, Douglas

    parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.

  17. 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.

  18. Predictor-Based Model Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  19. Adaptive leadership framework for chronic illness: framing a research agenda for transforming care delivery.

    PubMed

    Anderson, Ruth A; Bailey, Donald E; Wu, Bei; Corazzini, Kirsten; McConnell, Eleanor S; Thygeson, N Marcus; Docherty, Sharron L

    2015-01-01

    We propose the Adaptive Leadership Framework for Chronic Illness as a novel framework for conceptualizing, studying, and providing care. This framework is an application of the Adaptive Leadership Framework developed by Heifetz and colleagues for business. Our framework views health care as a complex adaptive system and addresses the intersection at which people with chronic illness interface with the care system. We shift focus from symptoms to symptoms and the challenges they pose for patients/families. We describe how providers and patients/families might collaborate to create shared meaning of symptoms and challenges to coproduce appropriate approaches to care. PMID:25647829

  20. Adaptive muffler based on controlled flow valves.

    PubMed

    Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij

    2015-06-01

    An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462

  1. Flight 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 testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight 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.

  2. Microsystem design framework based on tool adaptations and library developments

    NASA Astrophysics Data System (ADS)

    Karam, Jean Michel; Courtois, Bernard; Rencz, Marta; Poppe, Andras; Szekely, Vladimir

    1996-09-01

    Besides foundry facilities, Computer-Aided Design (CAD) tools are also required to move microsystems from research prototypes to an industrial market. This paper describes a Computer-Aided-Design Framework for microsystems, based on selected existing software packages adapted and extended for microsystem technology, assembled with libraries where models are available in the form of standard cells described at different levels (symbolic, system/behavioral, layout). In microelectronics, CAD has already attained a highly sophisticated and professional level, where complete fabrication sequences are simulated and the device and system operation is completely tested before manufacturing. In comparison, the art of microsystem design and modelling is still in its infancy. However, at least for the numerical simulation of the operation of single microsystem components, such as mechanical resonators, thermo-elements, elastic diaphragms, reliable simulation tools are available. For the different engineering disciplines (like electronics, mechanics, optics, etc) a lot of CAD-tools for the design, simulation and verification of specific devices are available, but there is no CAD-environment within which we could perform a (micro-)system simulation due to the different nature of the devices. In general there are two different approaches to overcome this limitation: the first possibility would be to develop a new framework tailored for microsystem-engineering. The second approach, much more realistic, would be to use the existing CAD-tools which contain the most promising features, and to extend these tools so that they can be used for the simulation and verification of microsystems and of the devices involved. These tools are assembled with libraries in a microsystem design environment allowing a continuous design flow. The approach is driven by the wish to make microsystems accessible to a large community of people, including SMEs and non-specialized academic institutions.

  3. Adaptive Impedance Control Of Redundant Manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun; Colbaugh, Richard D.; Glass, Kristin L.

    1994-01-01

    Improved method of controlling mechanical impedance of end effector of redundant robotic manipulator based on adaptive-control theory. Consists of two subsystems: adaptive impedance controller generating force-control inputs in Cartesian space of end effector to provide desired end-effector-impedance characteristics, and subsystem implementing algorithm that maps force-control inputs into torques applied to joints of manipulator. Accurate control of end effector and effective utilization of redundancy achieved simultaneously by use of method. Potential use to improve performance of such typical impedance-control tasks as deburring edges and accommodating transitions between unconstrained and constrained motions of end effectors.

  4. Adaptive spacecraft attitude control utilizing eigenaxis rotations

    NASA Technical Reports Server (NTRS)

    Cochran, J. E., Jr.; Colburn, B. K.; Speakman, N. O.

    1975-01-01

    Conventional and adaptive attitude control of spacecraft which use control moment gyros (CMG's) as torque sources are discussed. Control laws predicated on the assumption of a linear system are used since the spacecraft equations of motion are formulated in an 'eigenaxis system' so that they are essentially linear during 'slow' maneuvers even if large angles are involved. The overall control schemes are 'optimal' in several senses. Eigenaxis rotations and a weighted pseudo-inverse CMG steering law are used and, in the adaptive case, a Model Reference Adaptive System (MRAS) controller based on Liapunov's Second Method is adopted. To substantiate the theory, digital simulation results obtained using physical parameters of a Large Space Telescope type spacecraft are presented. These results indicate that an adaptive control law is often desirable.

  5. Modeling-Error-Driven Performance-Seeking Direct Adaptive Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John

    2008-01-01

    This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.

  6. An ontological knowledge framework for adaptive medical workflow.

    PubMed

    Dang, Jiangbo; Hedayati, Amir; Hampel, Ken; Toklu, Candemir

    2008-10-01

    As emerging technologies, semantic Web and SOA (Service-Oriented Architecture) allow BPMS (Business Process Management System) to automate business processes that can be described as services, which in turn can be used to wrap existing enterprise applications. BPMS provides tools and methodologies to compose Web services that can be executed as business processes and monitored by BPM (Business Process Management) consoles. Ontologies are a formal declarative knowledge representation model. It provides a foundation upon which machine understandable knowledge can be obtained, and as a result, it makes machine intelligence possible. Healthcare systems can adopt these technologies to make them ubiquitous, adaptive, and intelligent, and then serve patients better. This paper presents an ontological knowledge framework that covers healthcare domains that a hospital encompasses-from the medical or administrative tasks, to hospital assets, medical insurances, patient records, drugs, and regulations. Therefore, our ontology makes our vision of personalized healthcare possible by capturing all necessary knowledge for a complex personalized healthcare scenario involving patient care, insurance policies, and drug prescriptions, and compliances. For example, our ontology facilitates a workflow management system to allow users, from physicians to administrative assistants, to manage, even create context-aware new medical workflows and execute them on-the-fly.

  7. Chaotic satellite attitude control by adaptive approach

    NASA Astrophysics Data System (ADS)

    Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping

    2014-06-01

    In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.

  8. Adaptive Flight Control Research at NASA

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    2008-01-01

    A broad overview of current adaptive flight control research efforts at NASA is presented, as well as some more detailed discussion of selected specific approaches. The stated objective of the Integrated Resilient Aircraft Control Project, one of NASA s Aviation Safety programs, is to advance the state-of-the-art of adaptive controls as a design option to provide enhanced stability and maneuverability margins for safe landing in the presence of adverse conditions such as actuator or sensor failures. Under this project, a number of adaptive control approaches are being pursued, including neural networks and multiple models. Validation of all the adaptive control approaches will use not only traditional methods such as simulation, wind tunnel testing and manned flight tests, but will be augmented with recently developed capabilities in unmanned flight testing.

  9. Adaptive control of nonlinear systems with actuator failures and uncertainties

    NASA Astrophysics Data System (ADS)

    Tang, Xidong

    2005-11-01

    Actuator failures have damaging effect on the performance of control systems, leading to undesired system behavior or even instability. Actuator failures are unknown in terms of failure time instants, failure patterns, and failure parameters. For system safety and reliability, the compensation of actuator failures is of both theoretical and practical significance. This dissertation is to further the study of adaptive designs for actuator failure compensation to nonlinear systems. In this dissertation a theoretical framework for adaptive control of nonlinear systems with actuator failures and system uncertainties is established. The contributions are the development of new adaptive nonlinear control schemes to handle unknown actuator failures for convergent tracking performance, the specification of conditions as a guideline for applications and system designs, and the extension of the adaptive nonlinear control theory. In the dissertation, adaptive actuator failure compensation is studied for several classes of nonlinear systems. In particular, adaptive state feedback schemes are developed for feedback linearizable systems and parametric strict-feedback systems. Adaptive output feedback schemes are deigned for output-feedback systems and a class of systems with unknown state-dependent nonlinearities. Furthermore, adaptive designs are addressed for MIMO systems with actuator failures, based on two grouping techniques: fixed grouping and virtual grouping. Theoretical issues such as controller structures, actuation schemes, zero dynamics, observation, grouping conditions, closed-loop stability, and tracking performance are extensively investigated. For each scheme, design conditions are clarified, and detailed stability and performance analysis is presented. A variety of applications including a wing-rock model, twin otter aircraft, hypersonic aircraft, and cooperative multiple manipulators are addressed with simulation results showing the effectiveness of the

  10. Decentralized digital adaptive control of robot motion

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1990-01-01

    A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

  11. L1 adaptive output-feedback control architectures

    NASA Astrophysics Data System (ADS)

    Kharisov, Evgeny

    This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine

  12. Multiple model adaptive control with mixing

    NASA Astrophysics Data System (ADS)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  13. Climate change adaptation frameworks: an evaluation of plans for coastal Suffolk, UK

    NASA Astrophysics Data System (ADS)

    Armstrong, J.; Wilby, R.; Nicholls, R. J.

    2015-11-01

    This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: scenario-led (SL), vulnerability-led (VL) and decision-centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis of metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation of implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid, showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.

  14. Climate change adaptation frameworks: an evaluation of plans for coastal, Suffolk, UK

    NASA Astrophysics Data System (ADS)

    Armstrong, J.; Wilby, R.; Nicholls, R. J.

    2015-06-01

    This paper asserts that three principal frameworks for climate change adaptation can be recognised in the literature: Scenario-Led (SL), Vulnerability-Led (VL) and Decision-Centric (DC) frameworks. A criterion is developed to differentiate these frameworks in recent adaptation projects. The criterion features six key hallmarks as follows: (1) use of climate model information; (2) analysis metrics/units; (3) socio-economic knowledge; (4) stakeholder engagement; (5) adaptation implementation mechanisms; (6) tier of adaptation implementation. The paper then tests the validity of this approach using adaptation projects on the Suffolk coast, UK. Fourteen adaptation plans were identified in an online survey. They were analysed in relation to the hallmarks outlined above and assigned to an adaptation framework. The results show that while some adaptation plans are primarily SL, VL or DC, the majority are hybrid showing a mixture of DC/VL and DC/SL characteristics. Interestingly, the SL/VL combination is not observed, perhaps because the DC framework is intermediate and attempts to overcome weaknesses of both SL and VL approaches. The majority (57 %) of adaptation projects generated a risk assessment or advice notes. Further development of this type of framework analysis would allow better guidance on approaches for organisations when implementing climate change adaptation initiatives, and other similar proactive long-term planning.

  15. On fractional Model Reference Adaptive Control.

    PubMed

    Shi, Bao; Yuan, Jian; Dong, Chao

    2014-01-01

    This paper extends the conventional Model Reference Adaptive Control systems to fractional ones based on the theory of fractional calculus. A control law and an incommensurate fractional adaptation law are designed for the fractional plant and the fractional reference model. The stability and tracking convergence are analyzed using the frequency distributed fractional integrator model and Lyapunov theory. Moreover, numerical simulations of both linear and nonlinear systems are performed to exhibit the viability and effectiveness of the proposed methodology. PMID:24574897

  16. New synchronization criteria for memristor-based networks: adaptive control and feedback control schemes.

    PubMed

    Li, Ning; Cao, Jinde

    2015-01-01

    In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results.

  17. New synchronization criteria for memristor-based networks: adaptive control and feedback control schemes.

    PubMed

    Li, Ning; Cao, Jinde

    2015-01-01

    In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765

  18. The linked medical data access control framework.

    PubMed

    Kamateri, Eleni; Kalampokis, Evangelos; Tambouris, Efthimios; Tarabanis, Konstantinos

    2014-08-01

    The integration of medical data coming from multiple sources is important in clinical research. Amongst others, it enables the discovery of appropriate subjects in patient-oriented research and the identification of innovative results in epidemiological studies. At the same time, the integration of medical data faces significant ethical and legal challenges that impose access constraints. Some of these issues can be addressed by making available aggregated instead of raw record-level data. In many cases however, there is still a need for controlling access even to the resulting aggregated data, e.g., due to data provider's policies. In this paper we present the Linked Medical Data Access Control (LiMDAC) framework that capitalizes on Linked Data technologies to enable controlling access to medical data across distributed sources with diverse access constraints. The LiMDAC framework consists of three Linked Data models, namely the LiMDAC metadata model, the LiMDAC user profile model, and the LiMDAC access policy model. It also includes an architecture that exploits these models. Based on the framework, a proof-of-concept platform is developed and its performance and functionality are evaluated by employing two usage scenarios.

  19. Simple adaptive tracking control for mobile robots

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  20. An adaptive grid with directional control

    NASA Technical Reports Server (NTRS)

    Brackbill, J. U.

    1993-01-01

    An adaptive grid generator for adaptive node movement is here derived by combining a variational formulation of Winslow's (1981) variable-diffusion method with a directional control functional. By applying harmonic-function theory, it becomes possible to define conditions under which there exist unique solutions of the resulting elliptic equations. The results obtained for the grid generator's application to the complex problem posed by the fluid instability-driven magnetic field reconnection demonstrate one-tenth the computational cost of either a Eulerian grid or an adaptive grid without directional control.

  1. Genetic algorithms in adaptive fuzzy control

    NASA Technical Reports Server (NTRS)

    Karr, C. Lucas; Harper, Tony R.

    1992-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

  2. Adaptive Control for Microgravity Vibration Isolation System

    NASA Technical Reports Server (NTRS)

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2005-01-01

    Most active vibration isolation systems that try to a provide quiescent acceleration environment for space science experiments have utilized linear design methods. In this paper, we address adaptive control augmentation of an existing classical controller that employs a high-gain acceleration feedback together with a low-gain position feedback to center the isolated platform. The control design feature includes parametric and dynamic uncertainties because the hardware of the isolation system is built as a payload-level isolator, and the acceleration Sensor exhibits a significant bias. A neural network is incorporated to adaptively compensate for the system uncertainties, and a high-pass filter is introduced to mitigate the effect of the measurement bias. Simulations show that the adaptive control improves the performance of the existing acceleration controller and keep the level of the isolated platform deviation to that of the existing control system.

  3. 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.

  4. Intelligent Engine Systems: Adaptive Control

    NASA Technical Reports Server (NTRS)

    Gibson, Nathan

    2008-01-01

    We have studied the application of the baseline Model Predictive Control (MPC) algorithm to the control of main fuel flow rate (WF36), variable bleed valve (AE24) and variable stator vane (STP25) control of a simulated high-bypass turbofan engine. Using reference trajectories for thrust and turbine inlet temperature (T41) generated by a simulated new engine, we have examined MPC for tracking these two reference outputs while controlling a deteriorated engine. We have examined the results of MPC control for six different transients: two idle-to-takeoff transients at sea level static (SLS) conditions, one takeoff-to-idle transient at SLS, a Bode power command and reverse Bode power command at 20,000 ft/Mach 0.5, and a reverse Bode transient at 35,000 ft/Mach 0.84. For all cases, our primary focus was on the computational effort required by MPC for varying MPC update rates, control horizons, and prediction horizons. We have also considered the effects of these MPC parameters on the performance of the control, with special emphasis on the thrust tracking error, the peak T41, and the sizes of violations of the constraints on the problem, primarily the booster stall margin limit, which for most cases is the lone constraint that is violated with any frequency.

  5. Exposure Control Using Adaptive Multi-Stage Item Bundles.

    ERIC Educational Resources Information Center

    Luecht, Richard M.

    This paper presents a multistage adaptive testing test development paradigm that promises to handle content balancing and other test development needs, psychometric reliability concerns, and item exposure. The bundled multistage adaptive testing (BMAT) framework is a modification of the computer-adaptive sequential testing framework introduced by…

  6. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    NASA Astrophysics Data System (ADS)

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  7. Adaptive Inner-Loop Rover Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

    2006-01-01

    Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

  8. Adaptive Control Strategies for Flexible Robotic Arm

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1996-01-01

    The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

  9. Language control in bilinguals: The adaptive control hypothesis

    PubMed Central

    Abutalebi, Jubin

    2013-01-01

    Speech comprehension and production are governed by control processes. We explore their nature and dynamics in bilingual speakers with a focus on speech production. Prior research indicates that individuals increase cognitive control in order to achieve a desired goal. In the adaptive control hypothesis we propose a stronger hypothesis: Language control processes themselves adapt to the recurrent demands placed on them by the interactional context. Adapting a control process means changing a parameter or parameters about the way it works (its neural capacity or efficiency) or the way it works in concert, or in cascade, with other control processes (e.g., its connectedness). We distinguish eight control processes (goal maintenance, conflict monitoring, interference suppression, salient cue detection, selective response inhibition, task disengagement, task engagement, opportunistic planning). We consider the demands on these processes imposed by three interactional contexts (single language, dual language, and dense code-switching). We predict adaptive changes in the neural regions and circuits associated with specific control processes. A dual-language context, for example, is predicted to lead to the adaptation of a circuit mediating a cascade of control processes that circumvents a control dilemma. Effective test of the adaptive control hypothesis requires behavioural and neuroimaging work that assesses language control in a range of tasks within the same individual. PMID:25077013

  10. Adaptive output feedback control of flexible systems

    NASA Astrophysics Data System (ADS)

    Yang, Bong-Jun

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

  11. Adaptive Modal Identification for Flutter Suppression Control

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.

    2016-01-01

    In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

  12. An environmental decision framework applied to marine engine control technologies.

    PubMed

    Corbett, James J; Chapman, David

    2006-06-01

    This paper develops a decision framework for considering emission control technologies on marine engines, informed by standard decision theory, with an open structure that may be adapted by operators with specific vessel and technology attributes different from those provided here. Attributes relate objectives important to choosing control technologies with specific alternatives that may meet several of the objectives differently. The transparent framework enables multiple stakeholders to understand how different subjective judgments and varying attribute properties may result in different technology choices. Standard scoring techniques ensure that attributes are not biased by subjective scoring and that weights are the primary quantitative input where subjective preferences are exercised. An expected value decision structure is adopted that considers probabilities (likelihood) that a given alternative can meet its claims; alternative decision criteria are discussed. Capital and annual costs are combined using a net present value approach. An iterative approach is advocated that allows for screening and disqualifying alternatives that do not meet minimum conditions for acceptance, such as engine warranty or U.S. Coast Guard requirements. This decision framework assists vessel operators in considering explicitly important attributes and in representing choices clearly to other stakeholders concerned about reducing air pollution from vessels. This general decision structure may also be applied similarly to other environmental controls in marine applications.

  13. Adaptive neural control of aeroelastic response

    NASA Astrophysics Data System (ADS)

    Lichtenwalner, Peter F.; Little, Gerald R.; Scott, Robert C.

    1996-05-01

    The Adaptive Neural Control of Aeroelastic Response (ANCAR) program is a joint research and development effort conducted by McDonnell Douglas Aerospace (MDA) and the National Aeronautics and Space Administration, Langley Research Center (NASA LaRC) under a Memorandum of Agreement (MOA). The purpose of the MOA is to cooperatively develop the smart structure technologies necessary for alleviating undesirable vibration and aeroelastic response associated with highly flexible structures. Adaptive control can reduce aeroelastic response associated with buffet and atmospheric turbulence, it can increase flutter margins, and it may be able to reduce response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Phase I of the ANCAR program involved development and demonstration of a neural network-based semi-adaptive flutter suppression system which used a neural network for scheduling control laws as a function of Mach number and dynamic pressure. This controller was tested along with a robust fixed-gain control law in NASA's Transonic Dynamics Tunnel (TDT) utilizing the Benchmark Active Controls Testing (BACT) wing. During Phase II, a fully adaptive on-line learning neural network control system has been developed for flutter suppression which will be tested in 1996. This paper presents the results of Phase I testing as well as the development progress of Phase II.

  14. Robust, Practical Adaptive Control for Launch Vehicles

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  15. 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.

  16. Mechanisms of motor adaptation in reactive balance control.

    PubMed

    Welch, Torrence D J; Ting, Lena H

    2014-01-01

    Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM) excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations. PMID:24810991

  17. CCSDS Spacecraft Monitor and Control Service Framework

    NASA Technical Reports Server (NTRS)

    Merri, Mario; Schmidt, Michael; Ercolani, Alessandro; Dankiewicz, Ivan; Cooper, Sam; Thompson, Roger; Symonds, Martin; Oyake, Amalaye; Vaughs, Ashton; Shames, Peter

    2004-01-01

    This CCSDS paper presents a reference architecture and service framework for spacecraft monitoring and control. It has been prepared by the Spacecraft Monitoring and Control working group of the CCSDS Mission Operations and Information Management Systems (MOIMS) area. In this context, Spacecraft Monitoring and Control (SM&C) refers to end-to-end services between on- board or remote applications and ground-based functions responsible for mission operations. The scope of SM&C includes: 1) Operational Concept: definition of an operational concept that covers a set of standard operations activities related to the monitoring and control of both ground and space segments. 2) Core Set of Services: definition of an extensible set of services to support the operational concept together with its information model and behaviours. This includes (non exhaustively) ground systems such as Automatic Command and Control, Data Archiving and Retrieval, Flight Dynamics, Mission Planning and Performance Evaluation. 3) Application-layer information: definition of the standard information set to be exchanged for SM&C purposes.

  18. Adaptive control design for hysteretic smart systems

    NASA Astrophysics Data System (ADS)

    McMahan, Jerry A.; Smith, Ralph C.

    2011-04-01

    Ferroelectric and ferromagnetic actuators are being considered for a range of industrial, aerospace, aeronautic and biomedical applications due to their unique transduction capabilities. However, they also exhibit hysteretic and nonlinear behavior that must be accommodated in models and control designs. If uncompensated, these effects can yield reduced system performance and, in the worst case, can produce unpredictable behavior of the control system. In this paper, we address the development of adaptive control designs for hysteretic systems. We review an MRAC-like adaptive control algorithm used to track a reference trajectory while computing online estimates for certain model parameters. This method is incorporated in a composite control algorithm to improve the tracking capabilities of the system. Issues arising in the implementation of these algorithms are addressed, and a numerical example is presented, comparing the results of each method.

  19. Adaptive control of a robotic manipulator

    NASA Technical Reports Server (NTRS)

    Lewis, R. A.

    1977-01-01

    A control hierarchy for a robotic manipulator is described. The hierarchy includes perception and robot/environment interaction, the latter consisting of planning, path control, and terminal guidance loops. Environment-sensitive features include the provision of control governed by proximity, tactile, and visual sensors as well as the usual kinematic sensors. The manipulator is considered as part of an overall robot system. 'Adaptive control' in the present context refers to both the hierarchical nature of the control system and to its environment-responsive nature.

  20. Adaptive control of sulfur recovery units

    SciTech Connect

    Cunningham, D.B. )

    1994-08-01

    In a recent trial, adaptive control reduce the standard deviation of the tail gas ratio by 38%--increasing sulfur recovery efficiency by an estimated 0.3%. By using the controller on other control loops in the process, further increases are expected. Improved process control is a cost effective way to meet existing emissions limits. Future legislation will reduce the permissible emissions level, so it is imperative that existing sulfur recovery equipment by operated at peak efficiency. Peak efficiency can only be achieved with good trim air control, since it determines recovery efficiency. But process time delays and changes in the incoming gas stream make good control difficult to achieve. An adaptive controller is well suited to trim air control, since it can easily handle time delay sand adapt to changing process conditions. The improved efficiency is a considerable economic benefit to gas processing plants, since: (1) capital and operating expenses needed to improve recovery efficiency are avoided; (2) increased production is possible, since sulfur license limits are easier to meet; and (3) catalyst bed life is extended. Results of the test are discussed.

  1. 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.

  2. 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.

  3. Adaptive control system for gas producing wells

    SciTech Connect

    Fedor, Pashchenko; Sergey, Gulyaev; Alexander, Pashchenko

    2015-03-10

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation.

  4. Predictive Control of Speededness in Adaptive Testing

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    2009-01-01

    An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

  5. Robust Adaptive Control In Hilbert Space

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  6. Robust adaptive control of HVDC systems

    SciTech Connect

    Reeve, J.; Sultan, M. )

    1994-07-01

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

  7. Extending the Device Support for the ALMA Control Subsystem Code Generation Framework

    NASA Astrophysics Data System (ADS)

    Reveco, J.; Mora, M.; González, V.; Sáez, N.; Ibsen, J.; Staig, T.; Reyes, C.; Kern, J.; Juerges, T.

    2010-12-01

    The existing code generation framework in the ALMA Control subsystem provides basic and functional code for ALMA antenna devices using CAN bus as communication interface. There are also devices which use Ethernet communication. This paper explains how the code generation framework, based on openArchitectureWare, was extended to include the code generation of Ethernet control components, working on top of the ALMA Common Software (ACS) distributed control framework. In order to achieve this, a new datamodel and new class templates were created, and the device components design adapted.

  8. Adaptive Variable Bias Magnetic Bearing Control

    NASA Technical Reports Server (NTRS)

    Johnson, Dexter; Brown, Gerald V.; Inman, Daniel J.

    1998-01-01

    Most magnetic bearing control schemes use a bias current with a superimposed control current to linearize the relationship between the control current and the force it delivers. With the existence of the bias current, even in no load conditions, there is always some power consumption. In aerospace applications, power consumption becomes an important concern. In response to this concern, an alternative magnetic bearing control method, called Adaptive Variable Bias Control (AVBC), has been developed and its performance examined. The AVBC operates primarily as a proportional-derivative controller with a relatively slow, bias current dependent, time-varying gain. The AVBC is shown to reduce electrical power loss, be nominally stable, and provide control performance similar to conventional bias control. Analytical, computer simulation, and experimental results are presented in this paper.

  9. Adapted Fuzzy Controller for Astronomical Telescope Tracking

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah

    2004-04-01

    This paper presents a novel application of fuzzy logic (FL) controller driven by an adaptive fuzzy set (AFS) for position tracking of the telescope driven by electric motor. Also, the proposed FL controller, driven by AFS, is compared with a classical FL control, driven by a static fuzzy set (SFS). Both FL controllers algorithm use the position error and its rate of change as an input vector. The mathematical model of the telescope driven by electric motor is highly nonlinear differential equations. Therefore the use of the artificial intelligent controller, such as FL is much better than the conventional controller, to cover a wide range of operating conditions. So, the output of FL control is utilized to force the electric drives, of the telescope, to satisfy a perfect matching of the predefined desired position of the telescope arms. Both of FL controllers, using AFS and SFS, are simulated and tested when the system is subjected to a step change in reference value. In addition, these simulation results are compared with the conventional Proportional-Derivative (PD) controller, driven by fixed gain. The proposed FL, using an adaptive fuzzy set, improve the dynamic response of the overall system by improving the damping coefficient and decreasing the rise time and settling time compared with other two controllers.

  10. Software Framework for Controlling Unsupervised Scientific Instruments.

    PubMed

    Schmid, Benjamin; Jahr, Wiebke; Weber, Michael; Huisken, Jan

    2016-01-01

    Science outreach and communication are gaining more and more importance for conveying the meaning of today's research to the general public. Public exhibitions of scientific instruments can provide hands-on experience with technical advances and their applications in the life sciences. The software of such devices, however, is oftentimes not appropriate for this purpose. In this study, we describe a software framework and the necessary computer configuration that is well suited for exposing a complex self-built and software-controlled instrument such as a microscope to laymen under limited supervision, e.g. in museums or schools. We identify several aspects that must be met by such software, and we describe a design that can simultaneously be used to control either (i) a fully functional instrument in a robust and fail-safe manner, (ii) an instrument that has low-cost or only partially working hardware attached for illustration purposes or (iii) a completely virtual instrument without hardware attached. We describe how to assess the educational success of such a device, how to monitor its operation and how to facilitate its maintenance. The introduced concepts are illustrated using our software to control eduSPIM, a fluorescent light sheet microscope that we are currently exhibiting in a technical museum.

  11. Software Framework for Controlling Unsupervised Scientific Instruments

    PubMed Central

    Schmid, Benjamin; Jahr, Wiebke; Weber, Michael; Huisken, Jan

    2016-01-01

    Science outreach and communication are gaining more and more importance for conveying the meaning of today’s research to the general public. Public exhibitions of scientific instruments can provide hands-on experience with technical advances and their applications in the life sciences. The software of such devices, however, is oftentimes not appropriate for this purpose. In this study, we describe a software framework and the necessary computer configuration that is well suited for exposing a complex self-built and software-controlled instrument such as a microscope to laymen under limited supervision, e.g. in museums or schools. We identify several aspects that must be met by such software, and we describe a design that can simultaneously be used to control either (i) a fully functional instrument in a robust and fail-safe manner, (ii) an instrument that has low-cost or only partially working hardware attached for illustration purposes or (iii) a completely virtual instrument without hardware attached. We describe how to assess the educational success of such a device, how to monitor its operation and how to facilitate its maintenance. The introduced concepts are illustrated using our software to control eduSPIM, a fluorescent light sheet microscope that we are currently exhibiting in a technical museum. PMID:27570966

  12. Software Framework for Controlling Unsupervised Scientific Instruments.

    PubMed

    Schmid, Benjamin; Jahr, Wiebke; Weber, Michael; Huisken, Jan

    2016-01-01

    Science outreach and communication are gaining more and more importance for conveying the meaning of today's research to the general public. Public exhibitions of scientific instruments can provide hands-on experience with technical advances and their applications in the life sciences. The software of such devices, however, is oftentimes not appropriate for this purpose. In this study, we describe a software framework and the necessary computer configuration that is well suited for exposing a complex self-built and software-controlled instrument such as a microscope to laymen under limited supervision, e.g. in museums or schools. We identify several aspects that must be met by such software, and we describe a design that can simultaneously be used to control either (i) a fully functional instrument in a robust and fail-safe manner, (ii) an instrument that has low-cost or only partially working hardware attached for illustration purposes or (iii) a completely virtual instrument without hardware attached. We describe how to assess the educational success of such a device, how to monitor its operation and how to facilitate its maintenance. The introduced concepts are illustrated using our software to control eduSPIM, a fluorescent light sheet microscope that we are currently exhibiting in a technical museum. PMID:27570966

  13. Modeling and adaptive control of acoustic noise

    NASA Astrophysics Data System (ADS)

    Venugopal, Ravinder

    Active noise control is a problem that receives significant attention in many areas including aerospace and manufacturing. The advent of inexpensive high performance processors has made it possible to implement real-time control algorithms to effect active noise control. Both fixed-gain and adaptive methods may be used to design controllers for this problem. For fixed-gain methods, it is necessary to obtain a mathematical model of the system to design controllers. In addition, models help us gain phenomenological insights into the dynamics of the system. Models are also necessary to perform numerical simulations. However, models are often inadequate for the purpose of controller design because they involve parameters that are difficult to determine and also because there are always unmodeled effects. This fact motivates the use of adaptive algorithms for control since adaptive methods usually require significantly less model information than fixed-gain methods. The first part of this dissertation deals with derivation of a state space model of a one-dimensional acoustic duct. Two types of actuation, namely, a side-mounted speaker (interior control) and an end-mounted speaker (boundary control) are considered. The techniques used to derive the model of the acoustic duct are extended to the problem of fluid surface wave control. A state space model of small amplitude surfaces waves of a fluid in a rectangular container is derived and two types of control methods, namely, surface pressure control and map actuator based control are proposed and analyzed. The second part of this dissertation deals with the development of an adaptive disturbance rejection algorithm that is applied to the problem of active noise control. ARMARKOV models which have the same structure as predictor models are used for system representation. The algorithm requires knowledge of only one path of the system, from control to performance, and does not require a measurement of the disturbance nor

  14. Resilience Rather than Recovery: A Contextual Framework on Adaptation Following Bereavement

    ERIC Educational Resources Information Center

    Sandler, Irwin N.; Wolchik, Sharlene A.; Ayers, Tim S.

    2008-01-01

    Using a contextual resilience framework, the authors examine the processes whereby bereaved persons change over time. Rather than the concept recovery, the authors propose that the concept adaptation best captures the process of change following bereavement and that the desired outcome of such adaptation is denoted by the term resilience.…

  15. A Framework for Adaptive E-Learning Based on Distributed Re-Usable Learning Activities.

    ERIC Educational Resources Information Center

    Brusilovsky, Peter; Nijhavan, Hemanta

    This paper suggests that a way to the new generation of powerful E-learning systems starts on the crossroads of two emerging fields: courseware re-use and adaptive educational systems. The paper presents the KnowledgeTree, a framework for adaptive E-learning based on distributed re-usable learning activities currently under development. The goal…

  16. ActiveTutor: Towards More Adaptive Features in an E-Learning Framework

    ERIC Educational Resources Information Center

    Fournier, Jean-Pierre; Sansonnet, Jean-Paul

    2008-01-01

    Purpose: This paper aims to sketch the emerging notion of auto-adaptive software when applied to e-learning software. Design/methodology/approach: The study and the implementation of the auto-adaptive architecture are based on the operational framework "ActiveTutor" that is used for teaching the topic of computer science programming in first-grade…

  17. Multiple Adaptation Types with Mitigation: A Framework for Policy Analysis

    EPA Science Inventory

    Effective climate policy will consist of mitigation and adaptation implemented simultaneously in a policy portfolio to reduce the risks of climate change. The relative share of these responses will vary over time and will be adjusted in response to new information. Furthermore,...

  18. Adaptive control of Space Station with control moment gyros

    NASA Technical Reports Server (NTRS)

    Bishop, Robert H.; Paynter, Scott J.; Sunkel, John W.

    1992-01-01

    An adaptive approach to Space Station attitude control is investigated. The main components of the controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is a full-state feedback space station baseline control law. The control gain calculation is based on linear-quadratic regulator theory with eigenvalues placement in a vertical strip. The parameter identification scheme is a recursive extended Kalman filter that estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to estimate Space Station inertias accurately during nominal control moment gyro operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.

  19. Adaptive control strategies for flexible robotic arm

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1993-01-01

    The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity if not unstable closed-loop behavior. Therefore a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

  20. Adaptable and adaptive materials for light flux control

    NASA Astrophysics Data System (ADS)

    Sixou, Pierre; Magnaldo, A.; Nourry, J.; Laye, C.

    1996-04-01

    The purpose of this paper is to describe and examine properties of light flux control materials. Indeed, intelligent light flux control is necessary not only to improve everyday visual convenience but also in an economical point of view in order to reduce global home energetic cost. Several types of materials are good potential candidates for such functions: (1) The most well-known investigations concern inorganic materials such as tungsten or molybdenum oxides in which an electrochrom layer darkens when enriched in ions, and looses its color when impoverished. Unfortunately, at the moment, there is no convenient way to realize correct ions suppliers. Moreover, other drawbacks arise, such as poor reversibility, reactive interferences or a sensitivity of the material to its environment. These systems only need a low voltage level to work. But, their dynamic response, which is correlated to the component surface, is quite long. (2) At the present time, another attractive issue seems promising. More and more studies concern micro-composite liquid crystal films. For first, we shall remind their principles as well as their way of preparation. After having talked about their main advantages as intelligent materials, we shall discuss their control, their light flux adaptability, or their memory capabilities.

  1. Parallel computations and control of adaptive structures

    NASA Technical Reports Server (NTRS)

    Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)

    1991-01-01

    The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.

  2. Adaptive management of river flows in Europe: A transferable framework for implementation

    NASA Astrophysics Data System (ADS)

    Summers, M. F.; Holman, I. P.; Grabowski, R. C.

    2015-12-01

    The evidence base for defining flow regimes to support healthy river ecosystems is weak, as there are few studies which quantify the ecological impact associated with different degrees of hydrological alteration. As a result, river flow standards used to manage water abstraction are largely based on expert judgement. Planned adaptive management studies on multiple rivers under the European Water Framework Directive represent an opportunity to learn about ecological flow requirements and improve the quantitative evidence base. However, identifying clear ecological responses to flow alteration can be a significant challenge, because of the complexity of river systems and the other factors which may confound the response. This paper describes the Adaptive River Management (ARM) framework, a flexible framework for implementing adaptive management of river flows that is transferable to other regions of the world. Application of the framework will ensure that the effectiveness of implemented management actions is appraised and that transferable quantitative data are collected that can be used in other geographical regions.

  3. F-8C adaptive flight control laws

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Harvey, C. A.; Stein, G.; Carlson, D. N.; Hendrick, R. C.

    1977-01-01

    Three candidate digital adaptive control laws were designed for NASA's F-8C digital flyby wire aircraft. Each design used the same control laws but adjusted the gains with a different adaptative algorithm. The three adaptive concepts were: high-gain limit cycle, Liapunov-stable model tracking, and maximum likelihood estimation. Sensors were restricted to conventional inertial instruments (rate gyros and accelerometers) without use of air-data measurements. Performance, growth potential, and computer requirements were used as criteria for selecting the most promising of these candidates for further refinement. The maximum likelihood concept was selected primarily because it offers the greatest potential for identifying several aircraft parameters and hence for improved control performance in future aircraft application. In terms of identification and gain adjustment accuracy, the MLE design is slightly superior to the other two, but this has no significant effects on the control performance achievable with the F-8C aircraft. The maximum likelihood design is recommended for flight test, and several refinements to that design are proposed.

  4. A Conceptual Framework for Planning Systemic Human Adaptation to Global Warming.

    PubMed

    Tait, Peter W; Hanna, Elizabeth G

    2015-08-31

    Human activity is having multiple, inter-related effects on ecosystems. Greenhouse gas emissions persisting along current trajectories threaten to significantly alter human society. At 0.85 °C of anthropogenic warming, deleterious human impacts are acutely evident. Additional warming of 0.5 °C-1.0 °C from already emitted CO₂ will further intensify extreme heat and damaging storm events. Failing to sufficiently address this trend will have a heavy human toll directly and indirectly on health. Along with mitigation efforts, societal adaptation to a warmer world is imperative. Adaptation efforts need to be significantly upscaled to prepare society to lessen the public health effects of rising temperatures. Modifying societal behaviour is inherently complex and presents a major policy challenge. We propose a social systems framework for conceptualizing adaptation that maps out three domains within the adaptation policy landscape: acclimatisation, behavioural adaptation and technological adaptation, which operate at societal and personal levels. We propose that overlaying this framework on a systems approach to societal change planning methods will enhance governments' capacity and efficacy in strategic planning for adaptation. This conceptual framework provides a policy oriented planning assessment tool that will help planners match interventions to the behaviours being targeted for change. We provide illustrative examples to demonstrate the framework's application as a planning tool.

  5. A Conceptual Framework for Planning Systemic Human Adaptation to Global Warming.

    PubMed

    Tait, Peter W; Hanna, Elizabeth G

    2015-09-01

    Human activity is having multiple, inter-related effects on ecosystems. Greenhouse gas emissions persisting along current trajectories threaten to significantly alter human society. At 0.85 °C of anthropogenic warming, deleterious human impacts are acutely evident. Additional warming of 0.5 °C-1.0 °C from already emitted CO₂ will further intensify extreme heat and damaging storm events. Failing to sufficiently address this trend will have a heavy human toll directly and indirectly on health. Along with mitigation efforts, societal adaptation to a warmer world is imperative. Adaptation efforts need to be significantly upscaled to prepare society to lessen the public health effects of rising temperatures. Modifying societal behaviour is inherently complex and presents a major policy challenge. We propose a social systems framework for conceptualizing adaptation that maps out three domains within the adaptation policy landscape: acclimatisation, behavioural adaptation and technological adaptation, which operate at societal and personal levels. We propose that overlaying this framework on a systems approach to societal change planning methods will enhance governments' capacity and efficacy in strategic planning for adaptation. This conceptual framework provides a policy oriented planning assessment tool that will help planners match interventions to the behaviours being targeted for change. We provide illustrative examples to demonstrate the framework's application as a planning tool. PMID:26334285

  6. Model reference adaptive control of robots

    NASA Technical Reports Server (NTRS)

    Steinvorth, Rodrigo

    1991-01-01

    This project presents the results of controlling two types of robots using new Command Generator Tracker (CGT) based Direct Model Reference Adaptive Control (MRAC) algorithms. Two mathematical models were used to represent a single-link, flexible joint arm and a Unimation PUMA 560 arm; and these were then controlled in simulation using different MRAC algorithms. Special attention was given to the performance of the algorithms in the presence of sudden changes in the robot load. Previously used CGT based MRAC algorithms had several problems. The original algorithm that was developed guaranteed asymptotic stability only for almost strictly positive real (ASPR) plants. This condition is very restrictive, since most systems do not satisfy this assumption. Further developments to the algorithm led to an expansion of the number of plants that could be controlled, however, a steady state error was introduced in the response. These problems led to the introduction of some modifications to the algorithms so that they would be able to control a wider class of plants and at the same time would asymptotically track the reference model. This project presents the development of two algorithms that achieve the desired results and simulates the control of the two robots mentioned before. The results of the simulations are satisfactory and show that the problems stated above have been corrected in the new algorithms. In addition, the responses obtained show that the adaptively controlled processes are resistant to sudden changes in the load.

  7. Decentralized adaptive control designs and microstrip antennas for smart structures

    NASA Astrophysics Data System (ADS)

    Khorrami, Farshad; Jain, Sandeep; Das, Nirod K.

    1996-05-01

    Smart structures lend themselves naturally to a decentralized control design framework, especially with adaptation mechanisms. The main reason being that it is highly undesirable to connect all the sensors and actuators in a large structure to a central processor. It is rather desirable to have local decision-making at each smart patch. Furthermore, this local controllers should be easily `expandable' to `contractible.' This corresponds to the fact that addition/deletion of several smart patches should not require a total redesign of the control system. The decentralized control strategies advocated in this paper are of expandable/contractible type. On another front, we are considering utilization of micro-strip antennas for power transfer to and from smart structures. We have made preliminary contributions in this direction and further developments are underway. These approaches are being pursued for active vibration damping and noise cancellation via piezoelectric ceramics although the methodology is general enough to be applicable to other type of active structures.

  8. Adaptive control based on retrospective cost optimization

    NASA Technical Reports Server (NTRS)

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  9. Adaptive Control with Reference Model Modification

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

  10. Block adaptive rate controlled image data compression

    NASA Technical Reports Server (NTRS)

    Rice, R. F.; Hilbert, E.; Lee, J.-J.; Schlutsmeyer, A.

    1979-01-01

    A block adaptive rate controlled (BARC) image data compression algorithm is described. It is noted that in the algorithm's principal rate controlled mode, image lines can be coded at selected rates by combining practical universal noiseless coding techniques with block adaptive adjustments in linear quantization. Compression of any source data at chosen rates of 3.0 bits/sample and above can be expected to yield visual image quality with imperceptible degradation. Exact reconstruction will be obtained if the one-dimensional difference entropy is below the selected compression rate. It is noted that the compressor can also be operated as a floating rate noiseless coder by simply not altering the input data quantization. Here, the universal noiseless coder ensures that the code rate is always close to the entropy. Application of BARC image data compression to the Galileo orbiter mission of Jupiter is considered.

  11. Reusable rocket engine intelligent control system framework design, phase 2

    NASA Technical Reports Server (NTRS)

    Nemeth, ED; Anderson, Ron; Ols, Joe; Olsasky, Mark

    1991-01-01

    Elements of an advanced functional framework for reusable rocket engine propulsion system control are presented for the Space Shuttle Main Engine (SSME) demonstration case. Functional elements of the baseline functional framework are defined in detail. The SSME failure modes are evaluated and specific failure modes identified for inclusion in the advanced functional framework diagnostic system. Active control of the SSME start transient is investigated, leading to the identification of a promising approach to mitigating start transient excursions. Key elements of the functional framework are simulated and demonstration cases are provided. Finally, the advanced function framework for control of reusable rocket engines is presented.

  12. Adaptive Input Reconstruction with Application to Model Refinement, State Estimation, and Adaptive Control

    NASA Astrophysics Data System (ADS)

    D'Amato, Anthony M.

    Input reconstruction is the process of using the output of a system to estimate its input. In some cases, input reconstruction can be accomplished by determining the output of the inverse of a model of the system whose input is the output of the original system. Inversion, however, requires an exact and fully known analytical model, and is limited by instabilities arising from nonminimum-phase zeros. The main contribution of this work is a novel technique for input reconstruction that does not require model inversion. This technique is based on a retrospective cost, which requires a limited number of Markov parameters. Retrospective cost input reconstruction (RCIR) does not require knowledge of nonminimum-phase zero locations or an analytical model of the system. RCIR provides a technique that can be used for model refinement, state estimation, and adaptive control. In the model refinement application, data are used to refine or improve a model of a system. It is assumed that the difference between the model output and the data is due to an unmodeled subsystem whose interconnection with the modeled system is inaccessible, that is, the interconnection signals cannot be measured and thus standard system identification techniques cannot be used. Using input reconstruction, these inaccessible signals can be estimated, and the inaccessible subsystem can be fitted. We demonstrate input reconstruction in a model refinement framework by identifying unknown physics in a space weather model and by estimating an unknown film growth in a lithium ion battery. The same technique can be used to obtain estimates of states that cannot be directly measured. Adaptive control can be formulated as a model-refinement problem, where the unknown subsystem is the idealized controller that minimizes a measured performance variable. Minimal modeling input reconstruction for adaptive control is useful for applications where modeling information may be difficult to obtain. We demonstrate

  13. Durham adaptive optics real-time controller.

    PubMed

    Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy

    2010-11-10

    The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.

  14. A hierarchical framework for air traffic control

    NASA Astrophysics Data System (ADS)

    Roy, Kaushik

    Air travel in recent years has been plagued by record delays, with over $8 billion in direct operating costs being attributed to 100 million flight delay minutes in 2007. Major contributing factors to delay include weather, congestion, and aging infrastructure; the Next Generation Air Transportation System (NextGen) aims to alleviate these delays through an upgrade of the air traffic control system. Changes to large-scale networked systems such as air traffic control are complicated by the need for coordinated solutions over disparate temporal and spatial scales. Individual air traffic controllers must ensure aircraft maintain safe separation locally with a time horizon of seconds to minutes, whereas regional plans are formulated to efficiently route flows of aircraft around weather and congestion on the order of every hour. More efficient control algorithms that provide a coordinated solution are required to safely handle a larger number of aircraft in a fixed amount of airspace. Improved estimation algorithms are also needed to provide accurate aircraft state information and situational awareness for human controllers. A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation

  15. Model Adaptation for Prognostics in a Particle Filtering Framework

    NASA Technical Reports Server (NTRS)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  16. Enabling the dynamic coupling between sensor web and Earth system models - The Self-Adaptive Earth Predictive Systems (SEPS) framework

    NASA Astrophysics Data System (ADS)

    di, L.; Yu, G.; Chen, N.

    2007-12-01

    The self-adaptation concept is the central piece of the control theory widely and successfully used in engineering and military systems. Such a system contains a predictor and a measurer. The predictor takes initial condition and makes an initial prediction and the measurer then measures the state of a real world phenomenon. A feedback mechanism is built in that automatically feeds the measurement back to the predictor. The predictor takes the measurement against the prediction to calculate the prediction error and adjust its internal state based on the error. Thus, the predictor learns from the error and makes a more accurate prediction in the next step. By adopting the self-adaptation concept, we proposed the Self-adaptive Earth Predictive System (SEPS) concept for enabling the dynamic coupling between the sensor web and the Earth system models. The concept treats Earth System Models (ESM) and Earth Observations (EO) as integral components of the SEPS coupled by the SEPS framework. EO measures the Earth system state while ESM predicts the evolution of the state. A feedback mechanism processes EO measurements and feeds them into ESM during model runs or as initial conditions. A feed-forward mechanism analyzes the ESM predictions against science goals for scheduling optimized/targeted observations. The SEPS framework automates the Feedback and Feed-forward mechanisms (the FF-loop). Based on open consensus-based standards, a general SEPS framework can be developed for supporting the dynamic, interoperable coupling between ESMs and EO. Such a framework can support the plug-in-and-play capability of both ESMs and diverse sensors and data systems as long as they support the standard interfaces. This presentation discusses the SEPS concept, the service-oriented architecture (SOA) of SEPS framework, standards of choices for the framework, and the implementation. The presentation also presents examples of SEPS to demonstrate dynamic, interoperable, and live coupling of

  17. An framework for robust flight control design using constrained optimization

    NASA Technical Reports Server (NTRS)

    Palazoglu, A.; Yousefpor, M.; Hess, R. A.

    1992-01-01

    An analytical framework is described for the design of feedback control systems to meet specified performance criteria in the presence of structured and unstructured uncertainty. Attention is focused upon the linear time invariant, single-input, single-output problem for the purposes of exposition. The framework provides for control of the degree of the stabilizing compensator or controller.

  18. Genetic Adaptive Control for PZT Actuators

    NASA Technical Reports Server (NTRS)

    Kim, Jeongwook; Stover, Shelley K.; Madisetti, Vijay K.

    1995-01-01

    A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

  19. A Framework for Spatial Assessment of Local Level Vulnerability and Adaptive Capacity to Extreme Heat

    NASA Astrophysics Data System (ADS)

    Wilhelmi, O.; Hayden, M.; Harlan, S.; Ruddell, D.; Komatsu, K.; England, B.; Uejio, C.

    2008-12-01

    Changing climate is predicted to increase the intensity and impacts of heat waves prompting the need to develop preparedness and adaptation strategies that reduce societal vulnerability. Central to understanding societal vulnerability, is adaptive capacity, the potential of a system or population to modify its features/behaviors so as to better cope with existing and anticipated stresses and fluctuations. Adaptive capacity influences adaptation, the actual adjustments made to cope with the impacts from current and future hazardous heat events. Understanding societal risks, vulnerabilities and adaptive capacity to extreme heat events and climate change requires an interdisciplinary approach that includes information about weather and climate, the natural and built environment, social processes and characteristics, interactions with the stakeholders, and an assessment of community vulnerability. This project presents a framework for an interdisciplinary approach and a case study that explore linkages between quantitative and qualitative data for a more comprehensive understanding of local level vulnerability and adaptive capacity to extreme heat events in Phoenix, Arizona. In this talk, we will present a methodological framework for conducting collaborative research on societal vulnerability and adaptive capacity on a local level that includes integration of household surveys into a quantitative spatial assessment of societal vulnerability. We highlight a collaborative partnership among researchers, community leaders and public health officials. Linkages between assessment of local adaptive capacity and development of regional climate change adaptation strategies will be discussed.

  20. REVIEW: Internal models in sensorimotor integration: perspectives from adaptive control theory

    NASA Astrophysics Data System (ADS)

    Tin, Chung; Poon, Chi-Sang

    2005-09-01

    Internal models and adaptive controls are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models' architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods, such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning, are reviewed and their possible relevance to motor control is discussed. Possible applicability of a Luenberger observer and an extended Kalman filter to state estimation problems—such as sensorimotor prediction or the resolution of vestibular sensory ambiguity—is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal models in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future.

  1. Neural Control Adaptation to Motor Noise Manipulation.

    PubMed

    Hasson, Christopher J; Gelina, Olga; Woo, Garrett

    2016-01-01

    Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487

  2. Neural Control Adaptation to Motor Noise Manipulation

    PubMed Central

    Hasson, Christopher J.; Gelina, Olga; Woo, Garrett

    2016-01-01

    Antagonistic muscular co-activation can compensate for movement variability induced by motor noise at the expense of increased energetic costs. Greater antagonistic co-activation is commonly observed in older adults, which could be an adaptation to increased motor noise. The present study tested this hypothesis by manipulating motor noise in 12 young subjects while they practiced a goal-directed task using a myoelectric virtual arm, which was controlled by their biceps and triceps muscle activity. Motor noise was increased by increasing the coefficient of variation (CV) of the myoelectric signals. As hypothesized, subjects adapted by increasing antagonistic co-activation, and this was associated with reduced noise-induced performance decrements. A second hypothesis was that a virtual decrease in motor noise, achieved by smoothing the myoelectric signals, would have the opposite effect: co-activation would decrease and motor performance would improve. However, the results showed that a decrease in noise made performance worse instead of better, with no change in co-activation. Overall, these findings suggest that the nervous system adapts to virtual increases in motor noise by increasing antagonistic co-activation, and this preserves motor performance. Reducing noise may have failed to benefit performance due to characteristics of the filtering process itself, e.g., delays are introduced and muscle activity bursts are attenuated. The observed adaptations to increased noise may explain in part why older adults and many patient populations have greater antagonistic co-activation, which could represent an adaptation to increased motor noise, along with a desire for increased joint stability. PMID:26973487

  3. Active Inference, homeostatic regulation and adaptive behavioural control

    PubMed Central

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

    2015-01-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173

  4. Active Inference, homeostatic regulation and adaptive behavioural control.

    PubMed

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

    2015-11-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173

  5. A Conceptual Framework for Planning Systemic Human Adaptation to Global Warming

    PubMed Central

    Tait, Peter W.; Hanna, Elizabeth G.

    2015-01-01

    Human activity is having multiple, inter-related effects on ecosystems. Greenhouse gas emissions persisting along current trajectories threaten to significantly alter human society. At 0.85 °C of anthropogenic warming, deleterious human impacts are acutely evident. Additional warming of 0.5 °C–1.0 °C from already emitted CO2 will further intensify extreme heat and damaging storm events. Failing to sufficiently address this trend will have a heavy human toll directly and indirectly on health. Along with mitigation efforts, societal adaptation to a warmer world is imperative. Adaptation efforts need to be significantly upscaled to prepare society to lessen the public health effects of rising temperatures. Modifying societal behaviour is inherently complex and presents a major policy challenge. We propose a social systems framework for conceptualizing adaptation that maps out three domains within the adaptation policy landscape: acclimatisation, behavioural adaptation and technological adaptation, which operate at societal and personal levels. We propose that overlaying this framework on a systems approach to societal change planning methods will enhance governments’ capacity and efficacy in strategic planning for adaptation. This conceptual framework provides a policy oriented planning assessment tool that will help planners match interventions to the behaviours being targeted for change. We provide illustrative examples to demonstrate the framework’s application as a planning tool. PMID:26334285

  6. Robust adaptive control for Unmanned Aerial Vehicles

    NASA Astrophysics Data System (ADS)

    Kahveci, Nazli E.

    The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with

  7. Road map to adaptive optimal control. [jet engine control

    NASA Technical Reports Server (NTRS)

    Boyer, R.

    1980-01-01

    A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

  8. The US Forest Service Framework for Climate Adaptation (Invited)

    NASA Astrophysics Data System (ADS)

    Cleaves, D.

    2013-12-01

    Public lands are changing in response to climate change and related stressors such that resilience-based management plans that integrate climate-smart adaptation are needed. The goal of these plans is to facilitate land managers' consideration of a range of potential futures while simplifying the complex array of choices and assumptions in a rigorous, defensible manner. The foundation for climate response has been built into recent Forest Service policies, guidance, and strategies like the climate change Roadmap and Scorecard; 2012 Planning Rule; Cohesive Wildland Fire Management strategy; and Inventory, Monitoring & Assessment strategy. This has driven the need for information that is relevant, timely, and accessible to support vulnerability assessments and risk management to aid in designing and choosing alternatives and ranking actions. Managers must also consider carbon and greenhouse gas implications as well as understand the nature and level of uncertainties. The major adjustments that need to be made involve: improving risk-based decision making and working with predictive models and information; evaluating underlying assumptions against new realities and possibilities being revealed by climate science; integrating carbon cycle science and a new ethic of carbon stewardship into management practices; and preparing systems for inevitable changes to ameliorate negative effects, capture opportunities, or accept different and perhaps novel ecosystem configurations. We need to avoid waiting for complete science that never arrives and take actions that blend science and experience to boost learning, reduce costs and irreversible losses, and buy lead time.

  9. A Methodology for Investigating Adaptive Postural Control

    NASA Technical Reports Server (NTRS)

    McDonald, P. V.; Riccio, G. E.

    1999-01-01

    Our research on postural control and human-environment interactions provides an appropriate scientific foundation for understanding the skill of mass handling by astronauts in weightless conditions (e.g., extravehicular activity or EVA). We conducted an investigation of such skills in NASA's principal mass-handling simulator, the Precision Air-Bearing Floor, at the Johnson Space Center. We have studied skilled movement-body within a multidisciplinary context that draws on concepts and methods from biological and behavioral sciences (e.g., psychology, kinesiology and neurophysiology) as well as bioengineering. Our multidisciplinary research has led to the development of measures, for manual interactions between individuals and the substantial environment, that plausibly are observable by human sensory systems. We consider these methods to be the most important general contribution of our EVA investigation. We describe our perspective as control theoretic because it draws more on fundamental concepts about control systems in engineering than it does on working constructs from the subdisciplines of biomechanics and motor control in the bio-behavioral sciences. At the same time, we have attempted to identify the theoretical underpinnings of control-systems engineering that are most relevant to control by human beings. We believe that these underpinnings are implicit in the assumptions that cut across diverse methods in control-systems engineering, especially the various methods associated with "nonlinear control", "fuzzy control," and "adaptive control" in engineering. Our methods are based on these theoretical foundations rather than on the mathematical formalisms that are associated with particular methods in control-systems engineering. The most important aspects of the human-environment interaction in our investigation of mass handling are the functional consequences that body configuration and stability have for the pick up of information or the achievement of

  10. Justice and Equity Implications of Climate Change Adaptation: A Theoretical Evaluation Framework.

    PubMed

    Boeckmann, Melanie; Zeeb, Hajo

    2016-09-07

    Climate change affects human health, and climate change adaptation aims to reduce these risks through infrastructural, behavioral, and technological measures. However, attributing direct human health effects to climate change adaptation is difficult, causing an ethical dilemma between the need for evidence of strategies and their precautionary implementation before such evidence has been generated. In the absence of conclusive evidence for individual adaptation strategies, alternative approaches to the measurement of adaptation effectiveness need to be developed. This article proposes a theoretical framework and a set of guiding questions to assess effects of adaptation strategies on seven domains of health determinants, including social, economic, infrastructure, institutional, community, environmental, and cultural determinants of health. Its focus on advancing gender equity and environmental justice concurrently with the implementation of health-related adaptation could serve as a template for policymakers and researchers.

  11. Justice and Equity Implications of Climate Change Adaptation: A Theoretical Evaluation Framework

    PubMed Central

    Boeckmann, Melanie; Zeeb, Hajo

    2016-01-01

    Climate change affects human health, and climate change adaptation aims to reduce these risks through infrastructural, behavioral, and technological measures. However, attributing direct human health effects to climate change adaptation is difficult, causing an ethical dilemma between the need for evidence of strategies and their precautionary implementation before such evidence has been generated. In the absence of conclusive evidence for individual adaptation strategies, alternative approaches to the measurement of adaptation effectiveness need to be developed. This article proposes a theoretical framework and a set of guiding questions to assess effects of adaptation strategies on seven domains of health determinants, including social, economic, infrastructure, institutional, community, environmental, and cultural determinants of health. Its focus on advancing gender equity and environmental justice concurrently with the implementation of health-related adaptation could serve as a template for policymakers and researchers. PMID:27618121

  12. Justice and Equity Implications of Climate Change Adaptation: A Theoretical Evaluation Framework.

    PubMed

    Boeckmann, Melanie; Zeeb, Hajo

    2016-01-01

    Climate change affects human health, and climate change adaptation aims to reduce these risks through infrastructural, behavioral, and technological measures. However, attributing direct human health effects to climate change adaptation is difficult, causing an ethical dilemma between the need for evidence of strategies and their precautionary implementation before such evidence has been generated. In the absence of conclusive evidence for individual adaptation strategies, alternative approaches to the measurement of adaptation effectiveness need to be developed. This article proposes a theoretical framework and a set of guiding questions to assess effects of adaptation strategies on seven domains of health determinants, including social, economic, infrastructure, institutional, community, environmental, and cultural determinants of health. Its focus on advancing gender equity and environmental justice concurrently with the implementation of health-related adaptation could serve as a template for policymakers and researchers. PMID:27618121

  13. Adaptive Accommodation Control Method for Complex Assembly

    NASA Astrophysics Data System (ADS)

    Kang, Sungchul; Kim, Munsang; Park, Shinsuk

    Robotic systems have been used to automate assembly tasks in manufacturing and in teleoperation. Conventional robotic systems, however, have been ineffective in controlling contact force in multiple contact states of complex assemblythat involves interactions between complex-shaped parts. Unlike robots, humans excel at complex assembly tasks by utilizing their intrinsic impedance, forces and torque sensation, and tactile contact clues. By examining the human behavior in assembling complex parts, this study proposes a novel geometry-independent control method for robotic assembly using adaptive accommodation (or damping) algorithm. Two important conditions for complex assembly, target approachability and bounded contact force, can be met by the proposed control scheme. It generates target approachable motion that leads the object to move closer to a desired target position, while contact force is kept under a predetermined value. Experimental results from complex assembly tests have confirmed the feasibility and applicability of the proposed method.

  14. Controlling cluster synchronization by adapting the topology.

    PubMed

    Lehnert, Judith; Hövel, Philipp; Selivanov, Anton; Fradkov, Alexander; Schöll, Eckehard

    2014-10-01

    We suggest an adaptive control scheme for the control of in-phase and cluster synchronization in delay-coupled networks. Based on the speed-gradient method, our scheme adapts the topology of a network such that the target state is realized. It is robust towards different initial conditions as well as changes in the coupling parameters. The emerging topology is characterized by a delicate interplay of excitatory and inhibitory links leading to the stabilization of the desired cluster state. As a crucial parameter determining this interplay we identify the delay time. Furthermore, we show how to construct networks such that they exhibit not only a given cluster state but also with a given oscillation frequency. We apply our method to coupled Stuart-Landau oscillators, a paradigmatic normal form that naturally arises in an expansion of systems close to a Hopf bifurcation. The successful and robust control of this generic model opens up possible applications in a wide range of systems in physics, chemistry, technology, and life science.

  15. Kalman filter based control for Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Petit, Cyril; Quiros-Pacheco, Fernando; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Fusco, Thierry

    2004-12-01

    Classical Adaptive Optics suffer from a limitation of the corrected Field Of View. This drawback has lead to the development of MultiConjugated Adaptive Optics. While the first MCAO experimental set-ups are presently under construction, little attention has been paid to the control loop. This is however a key element in the optimization process especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications : simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering which seems a very promising solution. Following the work of Brice Leroux, we focus on a frequential characterization of kalman filters, computing a transfer matrix. The result brings much information about their behaviour and allows comparisons with classical controllers. It also appears that straightforward improvements of the system models can lead to static aberrations and vibrations filtering. Simulation results are proposed and analysed thanks to our frequential characterization. Related problems such as model errors, aliasing effect reduction or experimental implementation and testing of Kalman filter control loop on a simplified MCAO experimental set-up could be then discussed.

  16. Adaptive control: Stability, convergence, and robustness

    NASA Technical Reports Server (NTRS)

    Sastry, Shankar; Bodson, Marc

    1989-01-01

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

  17. Learning about colonization when managing metapopulations under an adaptive management framework.

    PubMed

    Southwell, Darren M; Hauser, Cindy E; McCarthy, Michael A

    2016-01-01

    Adaptive management is a framework for resolving key uncertainties while managing complex ecological systems. Its use has been prominent in fisheries research and wildlife harvesting; however, its application to other areas of environmental management remains somewhat limited. Indeed, adaptive management has not been used to guide and inform metapopulation restoration, despite considerable uncertainty surrounding such actions. In this study, we determined how best to learn about the colonization rate when managing metapopulations under an adaptive management framework. We developed a mainland-island metapopulation model based on the threatened bay checkerspot butterfly (Euphydryas editha bayensis) and assessed three management approaches: adding new patches, adding area to existing patches, and doing nothing. Using stochastic dynamic programming, we found the optimal passive and active adaptive management strategies by monitoring colonization of vacant patches. Under a passive adaptive strategy, increasing patch area was best when the expected colonization rate was below a threshold; otherwise, adding new patches was optimal. Under an active adaptive strategy, it was best to add patches only when we were reasonably confident that the colonization rate was high. This research provides a framework for managing mainland-island metapopulations in the face of uncertainty while learning about the dynamics of these complex systems. PMID:27039525

  18. 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.

  19. 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.

  20. Primer Control System Cyber Security Framework and Technical Metrics

    SciTech Connect

    Wayne F. Boyer; Miles A. McQueen

    2008-05-01

    The Department of Homeland Security National Cyber Security Division supported development of a control system cyber security framework and a set of technical metrics to aid owner-operators in tracking control systems security. The framework defines seven relevant cyber security dimensions and provides the foundation for thinking about control system security. Based on the developed security framework, a set of ten technical metrics are recommended that allow control systems owner-operators to track improvements or degradations in their individual control systems security posture.

  1. Kalman filtering to suppress spurious signals in Adaptive Optics control

    SciTech Connect

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  2. The reduced order model problem in distributed parameter systems adaptive identification and control. [adaptive control of flexible spacecraft

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.; Lawrence, D. A.

    1981-01-01

    The reduced order model problem in distributed parameter systems adaptive identification and control is investigated. A comprehensive examination of real-time centralized adaptive control options for flexible spacecraft is provided.

  3. Wavefront Control for Extreme Adaptive Optics

    SciTech Connect

    Poyneer, L A

    2003-07-16

    Current plans for Extreme Adaptive Optics systems place challenging requirements on wave-front control. This paper focuses on control system dynamics, wave-front sensing and wave-front correction device characteristics. It may be necessary to run an ExAO system after a slower, low-order AO system. Running two independent systems can result in very good temporal performance, provided specific design constraints are followed. The spatially-filtered wave-front sensor, which prevents aliasing and improves PSF sensitivity, is summarized. Different models of continuous and segmented deformable mirrors are studied. In a noise-free case, a piston-tip-tilt segmented MEMS device can achieve nearly equivalent performance to a continuous-sheet DM in compensating for a static phase aberration with use of spatial filtering.

  4. Adaptive Control of Flexible Structures Using Residual Mode Filters

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Frost, Susan

    2010-01-01

    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. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  5. Using a social justice and health framework to assess European climate change adaptation strategies.

    PubMed

    Boeckmann, Melanie; Zeeb, Hajo

    2014-11-28

    Climate change puts pressure on existing health vulnerabilities through higher frequency of extreme weather events, changes in disease vector distribution or exacerbated air pollution. Climate change adaptation policies may hold potential to reduce societal inequities. We assessed the role of public health and social justice in European climate change adaptation using a three-fold approach: a document analysis, a critical discourse analysis of a subgroup of strategies, and a ranking of strategies against our social justice framework. The ranking approach favored planning that includes various adaptation types, social issues and infrastructure changes. Themes on values identified in the five subgroup documents showed that risks are perceived as contradictory, technology is viewed as savior, responsibilities need to be negotiated, and social justice is advocated by only a few countries. Of 21 strategy documents assessed overall, those from Austria, England and Sweden received the highest scores in the ranking. Our qualitative assessment showed that in European adaptation planning, progress could still be made through community involvement into adaptation decisions, consistent consideration of social and demographic determinants, and a stronger link between infrastructural adaptation and the health sector. Overall, a social justice framework can serve as an evaluation guideline for adaptation policy documents.

  6. Using a Social Justice and Health Framework to Assess European Climate Change Adaptation Strategies

    PubMed Central

    Boeckmann, Melanie; Zeeb, Hajo

    2014-01-01

    Climate change puts pressure on existing health vulnerabilities through higher frequency of extreme weather events, changes in disease vector distribution or exacerbated air pollution. Climate change adaptation policies may hold potential to reduce societal inequities. We assessed the role of public health and social justice in European climate change adaptation using a three-fold approach: a document analysis, a critical discourse analysis of a subgroup of strategies, and a ranking of strategies against our social justice framework. The ranking approach favored planning that includes various adaptation types, social issues and infrastructure changes. Themes on values identified in the five subgroup documents showed that risks are perceived as contradictory, technology is viewed as savior, responsibilities need to be negotiated, and social justice is advocated by only a few countries. Of 21 strategy documents assessed overall, those from Austria, England and Sweden received the highest scores in the ranking. Our qualitative assessment showed that in European adaptation planning, progress could still be made through community involvement into adaptation decisions, consistent consideration of social and demographic determinants, and a stronger link between infrastructural adaptation and the health sector. Overall, a social justice framework can serve as an evaluation guideline for adaptation policy documents. PMID:25464133

  7. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  8. A Framework for Adaptable Operating and Runtime Systems

    SciTech Connect

    Sterling, Thomas

    2014-03-04

    The emergence of new classes of HPC systems where performance improvement is enabled by Moore’s Law for technology is manifest through multi-core-based architectures including specialized GPU structures. Operating systems were originally designed for control of uniprocessor systems. By the 1980s multiprogramming, virtual memory, and network interconnection were integral services incorporated as part of most modern computers. HPC operating systems were primarily derivatives of the Unix model with Linux dominating the Top-500 list. The use of Linux for commodity clusters was first pioneered by the NASA Beowulf Project. However, the rapid increase in number of cores to achieve performance gain through technology advances has exposed the limitations of POSIX general-purpose operating systems in scaling and efficiency. This project was undertaken through the leadership of Sandia National Laboratories and in partnership of the University of New Mexico to investigate the alternative of composable lightweight kernels on scalable HPC architectures to achieve superior performance for a wide range of applications. The use of composable operating systems is intended to provide a minimalist set of services specifically required by a given application to preclude overheads and operational uncertainties (“OS noise”) that have been demonstrated to degrade efficiency and operational consistency. This project was undertaken as an exploration to investigate possible strategies and methods for composable lightweight kernel operating systems towards support for extreme scale systems.

  9. Gradually Adaptive Frameworks: Reasonable Disagreement and the Evolution of Evaluative Systems in Music Education

    ERIC Educational Resources Information Center

    Haskins, Stanley

    2013-01-01

    The concept of "gradually adaptive frameworks" is introduced as a model with the potential to describe the evolution of belief evaluative systems through the consideration of reasonable arguments and evidence. This concept is demonstrated through an analysis of specific points of disagreement between David Elliott's praxial philosophy…

  10. Gradually Adaptive Frameworks: Reasonable Disagreement and the Evolution of Evaluative Systems in Music Education

    ERIC Educational Resources Information Center

    Haskins, Stanley

    2013-01-01

    The concept of "gradually adaptive frameworks" is introduced as a model with the potential to describe the evolution of belief evaluative systems through the consideration of reasonable arguments and evidence. This concept is demonstrated through an analysis of specific points of disagreement between David Elliott's praxial…

  11. Using a Vulnerability-Stress-Adaptation Framework to Predict Physical Aggression Trajectories in Newlywed Marriage

    ERIC Educational Resources Information Center

    Langer, Amie; Lawrence, Erika; Barry, Robin A.

    2008-01-01

    The authors used a vulnerability-stress-adaptation framework to examine personality traits and chronic stress as predictors of the developmental course of physical aggression in the early years of marriage. Additionally, personality traits and physical aggression were examined as predictors of the developmental course of chronic stress. Data from…

  12. Can Survival Processing Enhance Story Memory? Testing the Generalizability of the Adaptive Memory Framework

    ERIC Educational Resources Information Center

    Seamon, John G.; Bohn, Justin M.; Coddington, Inslee E.; Ebling, Maritza C.; Grund, Ethan M.; Haring, Catherine T.; Jang, Sue-Jung; Kim, Daniel; Liong, Christopher; Paley, Frances M.; Pang, Luke K.; Siddique, Ashik H.

    2012-01-01

    Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental survival…

  13. Transaction-Based Building Controls Framework, Volume 1: Reference Guide

    SciTech Connect

    Somasundaram, Sriram; Pratt, Robert G.; Akyol, Bora A.; Fernandez, Nicholas; Foster, Nikolas AF; Katipamula, Srinivas; Mayhorn, Ebony T.; Somani, Abhishek; Steckley, Andrew C.; Taylor, Zachary T.

    2014-12-01

    This document proposes a framework concept to achieve the objectives of raising buildings’ efficiency and energy savings potential benefitting building owners and operators. We call it a transaction-based framework, wherein mutually-beneficial and cost-effective market-based transactions can be enabled between multiple players across different domains. Transaction-based building controls are one part of the transactional energy framework. While these controls realize benefits by enabling automatic, market-based intra-building efficiency optimizations, the transactional energy framework provides similar benefits using the same market -based structure, yet on a larger scale and beyond just buildings, to the society at large.

  14. 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 constant…

  15. Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

    2016-09-01

    In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

  16. Real-Time Tracking Framework with Adaptive Features and Constrained Labels

    PubMed Central

    Li, Daqun; Xu, Tingfa; Chen, Shuoyang; Zhang, Jizhou; Jiang, Shenwang

    2016-01-01

    This paper proposes a novel tracking framework with adaptive features and constrained labels (AFCL) to handle illumination variation, occlusion and appearance changes caused by the variation of positions. The novel ensemble classifier, including the Forward–Backward error and the location constraint is applied, to get the precise coordinates of the promising bounding boxes. The Forward–Backward error can enhance the adaptation and accuracy of the binary features, whereas the location constraint can overcome the label noise to a certain degree. We use the combiner which can evaluate the online templates and the outputs of the classifier to accommodate the complex situation. Evaluation of the widely used tracking benchmark shows that the proposed framework can significantly improve the tracking accuracy, and thus reduce the processing time. The proposed framework has been tested and implemented on the embedded system using TMS320C6416 and Cyclone Ⅲ kernel processors. The outputs show that achievable and satisfying results can be obtained. PMID:27618052

  17. Real-Time Tracking Framework with Adaptive Features and Constrained Labels.

    PubMed

    Li, Daqun; Xu, Tingfa; Chen, Shuoyang; Zhang, Jizhou; Jiang, Shenwang

    2016-01-01

    This paper proposes a novel tracking framework with adaptive features and constrained labels (AFCL) to handle illumination variation, occlusion and appearance changes caused by the variation of positions. The novel ensemble classifier, including the Forward-Backward error and the location constraint is applied, to get the precise coordinates of the promising bounding boxes. The Forward-Backward error can enhance the adaptation and accuracy of the binary features, whereas the location constraint can overcome the label noise to a certain degree. We use the combiner which can evaluate the online templates and the outputs of the classifier to accommodate the complex situation. Evaluation of the widely used tracking benchmark shows that the proposed framework can significantly improve the tracking accuracy, and thus reduce the processing time. The proposed framework has been tested and implemented on the embedded system using TMS320C6416 and Cyclone Ⅲ kernel processors. The outputs show that achievable and satisfying results can be obtained. PMID:27618052

  18. 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.

  19. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    NASA Astrophysics Data System (ADS)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  20. 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.

  1. 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.

  2. Design of crashworthy structures with controlled behavior in HCA framework

    NASA Astrophysics Data System (ADS)

    Bandi, Punit

    The field of crashworthiness design is gaining more interest and attention from automakers around the world due to increasing competition and tighter safety norms. In the last two decades, topology and topometry optimization methods from structural optimization have been widely explored to improve existing designs or conceive new designs with better crashworthiness. Although many gradient-based and heuristic methods for topology- and topometry-based crashworthiness design are available these days, most of them result in stiff structures that are suitable only for a set of vehicle components in which maximizing the energy absorption or minimizing the intrusion is the main concern. However, there are some other components in a vehicle structure that should have characteristics of both stiffness and flexibility. Moreover, the load paths within the structure and potential buckle modes also play an important role in efficient functioning of such components. For example, the front bumper, side frame rails, steering column, and occupant protection devices like the knee bolster should all exhibit controlled deformation and collapse behavior. The primary objective of this research is to develop new methodologies to design crashworthy structures with controlled behavior. The well established Hybrid Cellular Automaton (HCA) method is used as the basic framework for the new methodologies, and compliant mechanism-type (sub)structures are the highlight of this research. The ability of compliant mechanisms to efficiently transfer force and/or motion from points of application of input loads to desired points within the structure is used to design solid and tubular components that exhibit controlled deformation and collapse behavior under crash loads. In addition, a new methodology for controlling the behavior of a structure under multiple crash load scenarios by adaptively changing the contributions from individual load cases is developed. Applied to practical design problems

  3. Verification and Tuning of an 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 focuses on the analysis and tuning of a controller based on the Adaptive Control Technology for Safe Flight (ACTS) architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller s ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft s state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.

  4. Stable adaptive fuzzy controllers with application to inverted pendulum tracking.

    PubMed

    Wang, L X

    1996-01-01

    An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given-trajectory. In this paper, two adaptive fuzzy controllers are designed based on the Lyapunov synthesis approach. We require that the final closed-loop system must be globally stable in the sense that all signals involved (states, controls, parameters, etc.) must be uniformly bounded. Roughly speaking, the adaptive fuzzy controllers are designed through the following steps: first, construct an initial controller based on linguistic descriptions (in the form of fuzzy IF-THEN rules) about the unknown plant from human experts; then, develop an adaptation law to adjust the parameters of the fuzzy controller on-line. We prove, for both adaptive fuzzy controllers, that: (1) all signals in the closed-loop systems are uniformly bounded; and (2) the tracking errors converge to zero under mild conditions. We provide the specific formulas of the bounds so that controller designers can determine the bounds based on their requirements. Finally, the adaptive fuzzy controllers are used to control the inverted pendulum to track a given trajectory, and the simulation results show that: (1) the adaptive fuzzy controllers can perform successful tracking without using any linguistic information; and (2) after incorporating some linguistic fuzzy rules into the controllers, the adaptation speed becomes faster and the tracking error becomes smaller.

  5. A Framework for Decomposition and Analysis of Agile Methodologies During Their Adaptation

    NASA Astrophysics Data System (ADS)

    Mikulenas, Gytenis; Kapocius, Kestutis

    In recent years there has been a steady increase of interest in Agile software development methodologies and techniques, which are often positioned as proven alternatives to the traditional plan-driven approaches. However, although there is no shortage of Agile methodologies to choose from, the formal methods for actually choosing or adapting the right one are lacking. The aim of the presented research was to define the formal way of preparing Agile methodologies for adaptation and creating an adaptation process framework. We argue that Agile methodologies can be successfully broken down into individual parts that can be specified on three different levels and later analyzed with regard to problem/concern areas. Results of such decomposition can form the foundation for the decisions on the adaptation of the specific Agile methodology. A case study is included in this chapter to further clarify the proposed approach.

  6. Enhancing learning, innovation, adaptation, and sustainability in health care organizations: the ELIAS performance management framework.

    PubMed

    Persaud, D David

    2014-01-01

    The development of sustainable health care organizations that provide high-quality accessible care is a topic of intense interest. This article provides a practical performance management framework that can be utilized to develop sustainable health care organizations. It is a cyclical 5-step process that is premised on accountability, performance management, and learning practices that are the foundation for a continuous process of measurement, disconfirmation, contextualization, implementation, and routinization This results in the enhancement of learning, innovation, adaptation, and sustainability (ELIAS). Important considerations such as recognizing that health care organizations are complex adaptive systems and the presence of a dynamic learning culture are necessary contextual factors that maximize the effectiveness of the proposed framework. Importantly, the ELIAS framework utilizes data that are already being collected by health care organizations for accountability, improvement, evaluation, and strategic purposes. Therefore, the benefit of the framework, when used as outlined, would be to enhance the chances of health care organizations achieving the goals of ongoing adaptation and sustainability, by design, rather than by chance.

  7. Combining analytical frameworks to assess livelihood vulnerability to climate change and analyse adaptation options☆

    PubMed Central

    Reed, M.S.; Podesta, G.; Fazey, I.; Geeson, N.; Hessel, R.; Hubacek, K.; Letson, D.; Nainggolan, D.; Prell, C.; Rickenbach, M.G.; Ritsema, C.; Schwilch, G.; Stringer, L.C.; Thomas, A.D.

    2013-01-01

    Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change. PMID:25844020

  8. A survey of adaptive control technology in robotics

    NASA Technical Reports Server (NTRS)

    Tosunoglu, S.; Tesar, D.

    1987-01-01

    Previous work on the adaptive control of robotic systems is reviewed. Although the field is relatively new and does not yet represent a mature discipline, considerable attention has been given to the design of sophisticated robot controllers. Here, adaptive control methods are divided into model reference adaptive systems and self-tuning regulators with further definition of various approaches given in each class. The similarity and distinct features of the designed controllers are delineated and tabulated to enhance comparative review.

  9. Full-Scale Flight Research Testbeds: Adaptive and Intelligent Control

    NASA Technical Reports Server (NTRS)

    Pahle, Joe W.

    2008-01-01

    This viewgraph presentation describes the adaptive and intelligent control methods used for aircraft survival. The contents include: 1) Motivation for Adaptive Control; 2) Integrated Resilient Aircraft Control Project; 3) Full-scale Flight Assets in Use for IRAC; 4) NASA NF-15B Tail Number 837; 5) Gen II Direct Adaptive Control Architecture; 6) Limited Authority System; and 7) 837 Flight Experiments. A simulated destabilization failure analysis along with experience and lessons learned are also presented.

  10. An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI.

    PubMed

    Churchill, Nathan W; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C

    2015-01-01

    BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the "pipeline") significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard "fixed" preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets.

  11. An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

    PubMed Central

    Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

    2015-01-01

    BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

  12. Accountability for quality of care: Monitoring all aspects of quality across a framework adapted for action.

    PubMed

    Hulton, Louise; Matthews, Zoë; Bandali, Sarah; Izge, Abubakar; Daroda, Ramatu; Stones, William

    2016-01-01

    Quality of care is essential to maternal and newborn survival. The multidimensional nature of quality of care means that frameworks are useful for capturing it. The present paper proposes an adaptation to a widely used quality of care framework for maternity services. The framework subdivides quality into two inter-related dimensions-provision and experience of care-but suggests adaptations to reflect changes in the concept of quality over the past 15years. The application of the updated framework is presented in a case study, which uses it to measure and inform quality improvements in northern Nigeria across the reproductive, maternal, newborn, and child health continuum of care. Data from 231 sampled basic and comprehensive emergency obstetric and newborn care (BEmONC and CEmONC) facilities in six northern Nigerian states showed that only 35%-47% of facilities met minimum quality standards in infrastructure. Standards for human resources performed better with 49%-73% reaching minimum standards. A framework like this could form the basis for a certification scheme. Certification offers a practical and concrete opportunity to drive quality standards up and reward good performance. It also offers a mechanism to strengthen accountability. PMID:26723043

  13. A Framework for Optimal Control Allocation with Structural Load Constraints

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc

    2010-01-01

    Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

  14. Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems.

    PubMed

    Wang, Chi-Hsu; Lin, Tsung-Chih; Lee, Tsu-Tian; Liu, Han-Leih

    2002-01-01

    A new hybrid direct/indirect adaptive fuzzy neural network (FNN) controller with a state observer and supervisory controller for a class of uncertain nonlinear dynamic systems is developed in this paper. The hybrid adaptive FNN controller, the free parameters of which can be tuned on-line by an observer-based output feedback control law and adaptive law, is a combination of direct and indirect adaptive FNN controllers. A weighting factor, which can be adjusted by the tradeoff between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive FNN controller and direct adaptive FNN controller. Furthermore, a supervisory controller is appended into the FNN controller to force the state to be within the constraint set. Therefore, if the FNN controller cannot maintain the stability, the supervisory controller starts working to guarantee stability. On the other hand, if the FNN controller works well, the supervisory controller will be deactivated. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. Two nonlinear systems, namely, inverted pendulum system and Chua's (1989) chaotic circuit, are fully illustrated to track sinusoidal signals. The resulting hybrid direct/indirect FNN control systems show better performances, i.e., tracking error and control effort can be made smaller and it is more flexible during the design process.

  15. Design Framework for an Adaptive MOOC Enhanced by Blended Learning: Supplementary Training and Personalized Learning for Teacher Professional Development

    ERIC Educational Resources Information Center

    Gynther, Karsten

    2016-01-01

    The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional development. The framework has been evaluated by…

  16. DEVS-based intelligent control of space adapted fluid mixing

    NASA Technical Reports Server (NTRS)

    Chi, Sung-Do; Zeigler, Bernard P.

    1990-01-01

    The development is described of event-based intelligent control system for a space-adapted mixing process by employing the DEVS (Discrete Event System Specification) formalism. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The DEVS-based intelligent control paradigm was applied in a space-adapted mixing system capable of supporting the laboratory automation aboard a Space Station.

  17. Least-Squares Adaptive Control Using Chebyshev Orthogonal Polynomials

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Burken, John; Ishihara, Abraham

    2011-01-01

    This paper presents a new adaptive control approach using Chebyshev orthogonal polynomials as basis functions in a least-squares functional approximation. The use of orthogonal basis functions improves the function approximation significantly and enables better convergence of parameter estimates. Flight control simulations demonstrate the effectiveness of the proposed adaptive control approach.

  18. Cancer Control Framework and Synthesis Rationale

    Cancer.gov

    Cancer control science is the conduct of basic and applied research in the behavioral, social, and population sciences to create or enhance interventions that, independently or in combination with biomedical approaches, reduce cancer risk, incidence, morbidity and mortality, and improve quality of life.

  19. Neural control of chronic stress adaptation

    PubMed Central

    Herman, James P.

    2013-01-01

    Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process. PMID:23964212

  20. Control of Flow Separation Using Adaptive Airfoils

    NASA Technical Reports Server (NTRS)

    Chandrasekhara, M. S.; Wilder, M. C.; Carr, L. W.; Davis, Sanford S. (Technical Monitor)

    1996-01-01

    A novel way of controlling flow separation is reported. The approach involves using an adaptive airfoil geometry that changes its leading edge shape to adjust to the instantaneous flow at high angles of attack such that the flow over it remains attached. In particular, a baseline NACA 0012 airfoil, whose leading edge curvature could be changed dynamically by 400% was tested under quasi-steady compressible flow conditions. A mechanical drive system was used to produce a rounded leading edge to reduce the strong local flow acceleration around its nose and thus reduce the strong adverse pressure gradient that follows such a rapid acceleration. Tests in steady flow showed that at M = 0.3, the flow separated at about 14 deg. angle of attack for the NACA 0012 profile but could be kept attached up to an angle of about 18 deg by changing the nose curvature. No significant hysteresis effects were observed; the flow could be made to reattach from its separated state at high angles by changing the leading edge curvature.

  1. Control of Flow Separation Using Adaptive Airfoils

    NASA Technical Reports Server (NTRS)

    Chandrasekhara, M. S.; Wilder, M. C.; Carr, L. W.; Davis, Sanford S. (Technical Monitor)

    1996-01-01

    A novel way of controlling flow separation is reported. The approach involves using an adaptive airfoil geometry that changes its leading edge shape to adjust to the instantaneous flow at high angles of attack such that the flow over it remains attached. In particular, a baseline NACA 0012 airfoil, whose leading edge curvature could be changed dynamically by 400% was tested under quasi-steady compressible flow conditions. A mechanical drive system was used to produce a rounded leading edge to reduce the strong local flow acceleration around its nose and thus reduce the strong adverse pressure gradient that follows such a rapid acceleration. Tests in steady flow showed that at M = 0.3, the flow separated at about 14 deg. angle of attack for the NACA 0012 profile but could be kept attached up to an angle of about 18 deg by changing the nose curvature. No significant hysteresis effects were observed; the flow could be made to reattach from its separated state at high angles by changing the leading edge curvature. Interestingly, the flow over a nearly semicircular nosed airfoil was separated even at low angles.

  2. Adaptive robust controller based on integral sliding mode concept

    NASA Astrophysics Data System (ADS)

    Taleb, M.; Plestan, F.

    2016-09-01

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

  3. Synthetic consciousness: the distributed adaptive control perspective.

    PubMed

    Verschure, Paul F M J

    2016-08-19

    Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID

  4. 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.

  5. Adaptive control system for large annular momentum control device

    NASA Technical Reports Server (NTRS)

    Montgomery, R. C.; Johnson, C. R., Jr.

    1981-01-01

    A dual momentum vector control concept, consisting of two counterrotating rings (each designated as an annular momentum control device), was studied for pointing and slewing control of large spacecraft. In a disturbance free space environment, the concept provides for three axis pointing and slewing capabilities while requiring no expendables. The approach utilizes two large diameter counterrotating rings or wheels suspended magnetically in many race supports distributed around the antenna structure. When the magnets are energized, attracting the two wheels, the resulting gyroscopic torque produces a rate along the appropriate axis. Roll control is provided by alternating the radiative rotational velocity of the two wheels. Wheels with diameters of 500 to 800 m and with sufficient momentum storage capability require rims only a few centimeters thick. The wheels are extremely flexible; therefore, it is necessary to account for the distributed nature of the rings in the design of the bearing controllers. Also, ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. An adaptive control system designed to handle these problems is described.

  6. Adaptive control of stochastic Hammerstein-Wiener nonlinear systems with measurement noise

    NASA Astrophysics Data System (ADS)

    Zhang, Bi; Mao, Zhizhong

    2016-01-01

    This paper deals with the adaptive control of a class of stochastic Hammerstein-Wiener nonlinear systems with measurement noise. Despite the fundamental progress achieved so far, a general theory framework about adaptive control of Hammerstein-Wiener models is still absent. Such situation is mainly due to the lack of an appropriate parameterisation model. To this end, this paper presents a novel parameterisation model that is to replace unmeasurable internal variables with their estimations. Then, the adaptive control algorithm to be applied is derived on the basis of self-tuning control. In addition, due to the use of the internal variable estimations, the stability and convergence properties are different from the self-tuning control. Our aim, in theoretical analysis, is to discover what limitations are in using the estimations instead of the true values in a control algorithm. Representative numerical examples are given and the simulation results verify the theoretical analysis.

  7. A service-oriented medical framework for fast and adaptive information delivery in mobile environment.

    PubMed

    Park, Eunjeong; Nam, Hyo Suk

    2009-11-01

    The need for fast treatment of patients in critical conditions motivates the use of mobile devices to provide prompt and consistent communication between hospitals and physicians. We propose a framework that supports ubiquitous access to medical systems using personalized mobile services and integrated medical systems. The proposed service-oriented medical framework provides dynamically composed services that are adapted to contextual variables such as the user's role, the network bandwidth, and resources available at mobile devices while supporting task allocation in distributed servers for massive resource-consuming services. It also manages accurate patient data by integrating local medical systems using medical information standards such as Digital Imaging and Communications in Medicine and Health Level 7. We have demonstrated the effectiveness of our framework by building a prototype of context-based adaptation of computerized tomography image retrieval for acute stroke treatments, which allows images to be viewed on mobile devices with WiMax wireless network. The proposed medical framework reduces hospital delays of patients and facilitates treatments in the absence of medical specialists. PMID:19775976

  8. A service-oriented medical framework for fast and adaptive information delivery in mobile environment.

    PubMed

    Park, Eunjeong; Nam, Hyo Suk

    2009-11-01

    The need for fast treatment of patients in critical conditions motivates the use of mobile devices to provide prompt and consistent communication between hospitals and physicians. We propose a framework that supports ubiquitous access to medical systems using personalized mobile services and integrated medical systems. The proposed service-oriented medical framework provides dynamically composed services that are adapted to contextual variables such as the user's role, the network bandwidth, and resources available at mobile devices while supporting task allocation in distributed servers for massive resource-consuming services. It also manages accurate patient data by integrating local medical systems using medical information standards such as Digital Imaging and Communications in Medicine and Health Level 7. We have demonstrated the effectiveness of our framework by building a prototype of context-based adaptation of computerized tomography image retrieval for acute stroke treatments, which allows images to be viewed on mobile devices with WiMax wireless network. The proposed medical framework reduces hospital delays of patients and facilitates treatments in the absence of medical specialists.

  9. AdaFF: Adaptive Failure-Handling Framework for Composite Web Services

    NASA Astrophysics Data System (ADS)

    Kim, Yuna; Lee, Wan Yeon; Kim, Kyong Hoon; Kim, Jong

    In this paper, we propose a novel Web service composition framework which dynamically accommodates various failure recovery requirements. In the proposed framework called Adaptive Failure-handling Framework (AdaFF), failure-handling submodules are prepared during the design of a composite service, and some of them are systematically selected and automatically combined with the composite Web service at service instantiation in accordance with the requirement of individual users. In contrast, existing frameworks cannot adapt the failure-handling behaviors to user's requirements. AdaFF rapidly delivers a composite service supporting the requirement-matched failure handling without manual development, and contributes to a flexible composite Web service design in that service architects never care about failure handling or variable requirements of users. For proof of concept, we implement a prototype system of the AdaFF, which automatically generates a composite service instance with Web Services Business Process Execution Language (WS-BPEL) according to the users' requirement specified in XML format and executes the generated instance on the ActiveBPEL engine.

  10. Experimental investigation of adaptive control of a parallel manipulator

    NASA Technical Reports Server (NTRS)

    Nguyen, Charles C.; Antrazi, Sami S.

    1992-01-01

    The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

  11. Adaptive Force Control For Compliant Motion Of A Robot

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1995-01-01

    Two adaptive control schemes offer robust solutions to problem of stable control of forces of contact between robotic manipulator and objects in its environment. They are called "adaptive admittance control" and "adaptive compliance control." Both schemes involve use of force-and torque sensors that indicate contact forces. These schemes performed well when tested in computational simulations in which they were used to control seven-degree-of-freedom robot arm in executing contact tasks. Choice between admittance or compliance control is dictated by requirements of the application at hand.

  12. A Novel Framework for Adaptation in Agriculture: Lessons Learned from California's Wine Industry (Invited)

    NASA Astrophysics Data System (ADS)

    Nicholas, K. A.

    2010-12-01

    While crop yields are threatened by climate change, the management decisions of growers, including their practices to modify the microclimate experienced by the crop, can partially or even completely offset these damages. However, there have been few evaluations of adaptation on the farm scale, where managers are on the front lines of responding to global change. I will present a framework for classifying potential adaptations based on their temporal and spatial scale, their ease of implementation, and their effectiveness in altering or maintaining crop production. Applying this framework to the winegrowing industry in California, it appears that many strategies suggested in the literature for adaptation will either be of limited effectiveness, likely to be cost-prohibitive, or are not compatible with the current values of growers. However, interviews with and observations of winegrowers reveal that novel adaptations, not widely discussed in the literature, are already being employed, often by individuals in an experimental capacity and without community coordination. For example, in addition to irrigation, water is used to modify the vine microclimate for both heating (frost protection) and evaporative cooling. An analysis of responses to past environmental stresses in the wine industry revealed that growers tended to respond to stresses individually rather than collectively, except for severe, novel pests and diseases. Responses may be reactive or proactive; most proactive strategies have been short-term, in response to imminent stress. Growers tend to rely on their own experience to guide their management decisions, which may offer poor guidance under novel climate regimes. These findings highlight some of the difficulties expected in adapting to global change, as well as areas for strategic investments to enhance agricultural resilience to climate change. In particular, strategies to enhance the potential for effective proactive, collective responses could

  13. CAreDroid: Adaptation Framework for Android Context-Aware Applications

    PubMed Central

    Elmalaki, Salma; Wanner, Lucas; Srivastava, Mani

    2015-01-01

    Context-awareness is the ability of software systems to sense and adapt to their physical environment. Many contemporary mobile applications adapt to changing locations, connectivity states, available computational and energy resources, and proximity to other users and devices. Nevertheless, there is little systematic support for context-awareness in contemporary mobile operating systems. Because of this, application developers must build their own context-awareness adaptation engines, dealing directly with sensors and polluting application code with complex adaptation decisions. In this paper, we introduce CAreDroid, which is a framework that is designed to decouple the application logic from the complex adaptation decisions in Android context-aware applications. In this framework, developers are required— only—to focus on the application logic by providing a list of methods that are sensitive to certain contexts along with the permissible operating ranges under those contexts. At run time, CAreDroid monitors the context of the physical environment and intercepts calls to sensitive methods, activating only the blocks of code that best fit the current physical context. CAreDroid is implemented as part of the Android runtime system. By pushing context monitoring and adaptation into the runtime system, CAreDroid eases the development of context-aware applications and increases their efficiency. In particular, case study applications implemented using CAre-Droid are shown to have: (1) at least half lines of code fewer and (2) at least 10× more efficient in execution time compared to equivalent context-aware applications that use only standard Android APIs. PMID:26834512

  14. Ocean Environmental Assessment and Adaptive Resource Management within the Framework of IOOS and CLEANER

    NASA Astrophysics Data System (ADS)

    Bonner, J.; Brezonik, P.; Clesceri, N.; Gouldman, C.; Jamail, R.; Zilkoski, D.

    2006-12-01

    The Integrated Ocean Observing System (IOOS), established through the efforts of the National Office for Integrated and Sustained Ocean Observations (Oceans.US) provides quality controlled data and information on a routine and continuous basis regarding current and future states of the oceans and Great Lakes at scales from global ocean basins to coastal ecosystems. The seven societal goals of IOOS are outlined in this paper. The Engineering and Geosciences Directorates at the National Science Foundation (NSF) are collaborating in planning the WATERS (WATer Environmental Research System) Network, an outgrowth of earlier, separate initiatives of the two directorates: CLEANER (Collaborative Large-scale Engineering Analysis Network for Environmental Research) and Hydrologic Observatories. WATERS Network is being developed by engineers and scientists in the academic community who recognize the need for an observation and research network to enable better understanding of human-dominated water-environments, their stressors, and the links between them. The WATERS Network model is based on a research framework anchored in a distributed, cyber-based network supporting: 1) data collection; 2) data aggregation; 3) analytical and exploratory tools; and 4) a computational environment supporting predictive modeling and policy analysis on water resource systems. Within IOOS, the U.S. coastal margin is divided into Regional Associations (RAs), organizational units that are conceptually linked through planned data collection and analysis activities for resolving fundamental coastal margin ecosystem questions and addressing RA concerns. Under the WATERS Network scheme, a Coastal Margin Regional Environmental System (RES) for coastal areas would be defined conceptually based on geomorphologic considerations of four major water bodies; Atlantic and Pacific Oceans, Gulf of Mexico, and Laurentian Great Lakes. Within this framework, each coastal margin would operate one or more local

  15. Framework Based Guidance Navigation and Control Flight Software Development

    NASA Technical Reports Server (NTRS)

    McComas, David

    2007-01-01

    This viewgraph presentation describes NASA's guidance navigation and control flight software development background. The contents include: 1) NASA/Goddard Guidance Navigation and Control (GN&C) Flight Software (FSW) Development Background; 2) GN&C FSW Development Improvement Concepts; and 3) GN&C FSW Application Framework.

  16. Adaptive robust control of the EBR-II reactor

    SciTech Connect

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

    1996-05-01

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

  17. 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.

  18. A health impact assessment framework for assessing vulnerability and adaptation planning for climate change.

    PubMed

    Brown, Helen; Spickett, Jeffery; Katscherian, Dianne

    2014-12-12

    This paper presents a detailed description of an approach designed to investigate the application of the Health Impact Assessment (HIA) framework to assess the potential health impacts of climate change. A HIA framework has been combined with key climate change terminology and concepts. The fundamental premise of this framework is an understanding of the interactions between people, the environment and climate. The diversity and complexity of these interactions can hinder much needed action on the critical health issue of climate change. The objectives of the framework are to improve the methodology for understanding and assessing the risks associated with potential health impacts of climate change, and to provide decision-makers with information that can facilitate the development of effective adaptation plans. While the process presented here provides guidance with respect to this task it is not intended to be prescriptive. As such, aspects of the process can be amended to suit the scope and available resources of each project. A series of working tables has been developed to assist in the collation of evidence throughout the process. The framework has been tested in a number of locations including Western Australia, Solomon Islands, Vanuatu and Nauru.

  19. A Health Impact Assessment Framework for Assessing Vulnerability and Adaptation Planning for Climate Change

    PubMed Central

    Brown, Helen; Spickett, Jeffery; Katscherian, Dianne

    2014-01-01

    This paper presents a detailed description of an approach designed to investigate the application of the Health Impact Assessment (HIA) framework to assess the potential health impacts of climate change. A HIA framework has been combined with key climate change terminology and concepts. The fundamental premise of this framework is an understanding of the interactions between people, the environment and climate. The diversity and complexity of these interactions can hinder much needed action on the critical health issue of climate change. The objectives of the framework are to improve the methodology for understanding and assessing the risks associated with potential health impacts of climate change, and to provide decision-makers with information that can facilitate the development of effective adaptation plans. While the process presented here provides guidance with respect to this task it is not intended to be prescriptive. As such, aspects of the process can be amended to suit the scope and available resources of each project. A series of working tables has been developed to assist in the collation of evidence throughout the process. The framework has been tested in a number of locations including Western Australia, Solomon Islands, Vanuatu and Nauru. PMID:25514146

  20. 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.

  1. An adaptive control scheme for coordinated multimanipulator systems

    SciTech Connect

    Jonghann Jean; Lichen Fu . Dept. of Electrical Engineering)

    1993-04-01

    The problem of adaptive coordinated control of multiple robot arms transporting an object is addressed. A stable adaptive control scheme for both trajectory tracking and internal force control is presented. Detailed analyses on tracking properties of the object position, velocity and the internal forces exerted on the object are given. It is shown that this control scheme can achieve satisfactory tracking performance without using the measurement of contact forces and their derivatives. It can be shown that this scheme can be realized by decentralized implementation to reduce the computational burden. Moreover, some efficient adaptive control strategies can be incorporated to reduce the computational complexity.

  2. 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.

  3. Adaptive jitter control for tracker line of sight stabilization

    NASA Astrophysics Data System (ADS)

    Gibson, Steve; Tsao, Tsu-Chin; Herrick, Dan; Beairsto, Christopher; Grimes, Ronnie; Harper, Todd; Radtke, Jeff; Roybal, Benito; Spray, Jay; Squires, Stephen; Tellez, Dave; Thurston, Michael

    2010-08-01

    A field test experiment on a range tracking telescope at the U. S. Army's White Sands Missile Range is exploring the use of recently developed adaptive control methods to minimize track loop jitter. Gimbal and platform vibration are the main sources of jitter in the experiments, although atmospheric turbulence also is a factor. In initial experiments, the adaptive controller reduced the track loop jitter significantly in frequency ranges beyond the bandwidth of the existing track loop. This paper presents some of the initial experimental results along with analysis of the performance of the adaptive control loop. The paper also describes the adaptive control scheme, its implementation on the WSMR telescope and the system identification required for adaptive control.

  4. Adaptive sliding mode control for a class of chaotic systems

    SciTech Connect

    Farid, R.; Ibrahim, A.; Zalam, B.

    2015-03-30

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  5. Toward a systems- and control-oriented agent framework.

    PubMed

    Fregene, Kingsley; Kennedy, Diane C; Wang, David W L

    2005-10-01

    This paper develops a systems- and control-oriented intelligent agent framework called the hybrid intelligent control agent (HICA), as well as its composition into specific kinds of multiagent systems. HICA is essentially developed around a hybrid control system core so that knowledge-based planning and coordination can be integrated with verified hybrid control primitives to achieve the coordinated control of multiple multimode dynamical systems. The scheme is applied to the control of teams of unmanned air and ground vehicles engaged in a pursuit-evasion war game. Results are demonstrated in simulation.

  6. Systems and Methods for Derivative-Free Adaptive Control

    NASA Technical Reports Server (NTRS)

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  7. Optimal stochastic control in natural resource management: Framework and examples

    USGS Publications Warehouse

    Williams, B.K.

    1982-01-01

    A framework is presented for the application of optimal control methods to natural resource problems. An expression of the optimal control problem appropriate for renewable natural resources is given and its application to Markovian systems is presented in some detail. Three general approaches are outlined for determining optimal control of infinite time horizon systems and three examples from the natural resource literature are used for illustration.

  8. A new approach to adaptive control of manipulators

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1987-01-01

    An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

  9. Adaptive control with variable dead-zone nonlinearities

    NASA Technical Reports Server (NTRS)

    Orlicki, D.; Valavani, L.; Athans, M.; Stein, G.

    1984-01-01

    It has been found that fixed error dead-zones as defined in the existing literature result in serious degradation of performance, due to the conservativeness which characterizes the determination of their width. In the present paper, variable width dead-zones are derived for the adaptive control of plants with unmodeled dynamics. The derivation makes use of information available about the unmodeled dynamics both a priori as well as during the adaptation process, so as to stabilize the adaptive loop and at the same time overcome the conservativeness and performance limitations of fixed-dead zone adaptive or fixed gain controllers.

  10. Projection Operator: A Step Towards Certification of Adaptive Controllers

    NASA Technical Reports Server (NTRS)

    Larchev, Gregory V.; Campbell, Stefan F.; Kaneshige, John T.

    2010-01-01

    One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

  11. Hormesis and adaptive cellular control systems

    EPA Science Inventory

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  12. An adaptive P300-based control system

    NASA Astrophysics Data System (ADS)

    Jin, Jing; Allison, Brendan Z.; Sellers, Eric W.; Brunner, Clemens; Horki, Petar; Wang, Xingyu; Neuper, Christa

    2011-06-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e. 12 columns and 7 rows). The 9- and 14-flash A and B paradigms present all items of the 12 × 7 matrix three times using either 9 or 14 flashes (instead of 19), decreasing the amount of time to present stimuli. Compared to 9-flash A, 9-flash B decreased the likelihood that neighboring items would flash when the target was not flashing, thereby reducing the interference from items adjacent to targets. 14-flash A also reduced the adjacent item interference and 14-flash B additionally eliminated successive (double) flashes of the same item. Results showed that the accuracy and bit rate of the adaptive system were higher than those of the non-adaptive system. In addition, 9- and 14-flash B produced significantly higher performance than their respective A conditions. The results also show the trend that the 14-flash B paradigm was better than the 19-flash pattern for naive users.

  13. AFECS. Multi-Agent Framework for Experiment Control Systems

    SciTech Connect

    Vardan Gyurjyan; David Abbott; William Heyes; Edward Jastrzembski; Carl Timmer; Elliott Wolin

    2008-01-23

    AFECS is a pure Java based software framework for designing and implementing distributed control systems. AFECS creates a control system environment as a collection of software agents behaving as finite state machines. These agents can represent real entities, such as hardware devices, software tasks, or control subsystems. A special control oriented ontology language (COOL), based on RDFS (Resource Definition Framework Schema) is provided for control system description as well as for agent communication. AFECS agents can be distributed over a variety of platforms. Agents communicate with their associated physical components using range of communication protocols, including tcl-DP, cMsg (publish-subscribe communication system developed at Jefferson Lab), SNMP (simple network management protocol), EPICS channel access protocol and JDBC.

  14. A framework for control simulations using the TRANSP code

    NASA Astrophysics Data System (ADS)

    Boyer, Mark D.; Andre, Rob; Gates, David; Gerhardt, Stefan; Goumiri, Imene; Menard, Jon

    2014-10-01

    The high-performance operational goals of present-day and future tokamaks will require development of advanced feedback control algorithms. Though reduced models are often used for initial designs, it is important to study the performance of control schemes with integrated models prior to experimental implementation. To this end, a flexible framework for closed loop simulations within the TRANSP code is being developed. The framework exploits many of the predictive capabilities of TRANSP and provides a means for performing control calculations based on user-supplied data (controller matrices, target waveforms, etc.). These calculations, along with the acquisition of ``real-time'' measurements and manipulation of TRANSP internal variables based on actuator requests, are implemented through a hook that allows custom run-specific code to be inserted into the standard TRANSP source code. As part of the framework, a module has been created to constrain the thermal stored energy in TRANSP using a confinement scaling expression. Progress towards feedback control of the current profile on NSTX-U will be presented to demonstrate the framework. Supported in part by an appointment to the U.S. Department of Energy Fusion Energy Postdoctoral Research Program administered by the Oak Ridge Institute for Science and Education.

  15. Adapting a theoretical framework for characterizing students' use of equations in physics problem solving

    NASA Astrophysics Data System (ADS)

    Rebello, Carina M.; Rebello, N. Sanjay

    2012-02-01

    Previous studies have focused on the resources that students activate and utilize while solving a given physics problem. However, few studies explore how students relate a given resource such as an equation, to various types of physics problems and contexts and how they ascertain the meaning and applicability of that resource. We explore how students view physics equations, derive meaning from those equations, and use those equations in physics problem solving. We adapt Dubinsky and McDonald's description of APOS (action-process-object-schema) theory of learning in mathematics, to construct a theoretical framework that describes how students interpret and use equations in physics in terms of actions, processes, objects, and schemas. This framework provides a lens for understanding how students construct their understanding of physics concepts and their relation to equations. We highlight how APOS theory can be operationalized to serve as a lens for studying the use of mathematics in physics problem solving.

  16. Cyclone preparedness and response: an analysis of lessons identified using an adapted military planning framework.

    PubMed

    Tatham, Peter; Oloruntoba, Richard; Spens, Karen

    2012-01-01

    The United Kingdom uses the Defence Lines of Development (DLOD) framework to analyse and understand the key components and costs of a military capability. Rooted in the Resource Based View (RBV) of a firm, an adapted DLOD approach is employed to explore, analyse and discuss the preparedness, planning and response strategies of two markedly different countries (Australia and Bangladesh) when faced with a major cyclone event of a comparable size. Given the numerous similarities in the challenges facing military forces in a complex emergency and humanitarian agencies in a natural disaster, the paper demonstrates the applicability of the DLOD framework as an analysis and planning tool in the cyclone preparedness planning and response phases, and more broadly within the disaster management area. In addition, the paper highlights the benefit to disaster managers, policymakers and researchers of exploiting comparative cross-learning opportunities from disaster events, drawn from different sectors and countries.

  17. A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity.

    PubMed

    Burton, A Cole; Huggard, David; Bayne, Erin; Schieck, Jim; Sólymos, Péter; Muhly, Tyler; Farr, Dan; Boutin, Stan

    2014-06-01

    Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors - thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance - or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human "footprint" and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.

  18. An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

    PubMed

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  19. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    PubMed Central

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  20. Adaptive torque control of variable speed wind turbines

    NASA Astrophysics Data System (ADS)

    Johnson, Kathryn E.

    Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.

  1. A framework for plot control in interactive story systems

    SciTech Connect

    Sgouros, N.M.; Papakonstantinou, G.; Tsanakas, P.

    1996-12-31

    This paper presents a framework for plot control in interactive story systems. In this framework, the user takes the place of the main character of the story, the protagonist. The rest of the cast consists of discrete characters, each playing a specific role in the story. A separate module in this system, the plot manager, controls the behavior of the cast and specifies what the protagonist can do. The story plot is dynamically shaped by the interference between cast members and their social interactions. The system accepts as input a story map which provides the main metaphor for organizing the plot and localizes the interaction of the protagonist with the rest of the cast. We are implementing this framework in PEGASUS, an interactive travel story environment for Greek mythology.

  2. Shaping the Cities of Tomorrow: Integrating Local Urban Adaptation within an Environmental Framework

    NASA Astrophysics Data System (ADS)

    Georgescu, M.

    2014-12-01

    Contemporary methods focused on increasing urban sustainability are largely based on the reduction of greenhouse gas emissions. While these efforts are essential steps forward, continued characterization of urban sustainability solely within a biogeochemical framework, with neglect of the biophysical impact of the built environment, omits regional hydroclimatic forcing of the same order of magnitude as greenhouse gas emissions. Using a suite of continuous, multi-year and multi-member continental scale numerical simulations with the WRF model for the U.S., we examine hydroclimatic impacts for a variety of U.S. urban expansion scenarios (for the year 2100) and urban adaptation futures (cool roofs, green roofs, and a hypothetical hybrid approach integrating biophysical properties of both cool and green roofs), and compare those to experiments utilizing a contemporary urban extent. Widespread adoption of adaptation strategies exhibits regionally and seasonally dependent hydroclimatic impacts. For some regions and seasons, urban-induced warming in excess of 3°C can be completely offset by all adaptation approaches examined. For other regions, widespread adoption of some adaptation approaches leads to significant rainfall decline. Sustainable urban expansion therefore requires an integrated assessment that also incorporates biophysically induced urban impacts, and demands tradeoff assessment of various strategies aimed to ameliorate deleterious consequences of growth (e.g., urban heat island reduction).

  3. Adaptive Fuzzy Control of a Direct Drive Motor

    NASA Technical Reports Server (NTRS)

    Medina, E.; Kim, Y. T.; Akbaradeh-T., M. -R.

    1997-01-01

    This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is verified by simulation results.

  4. Adaptive Fuzzy Control of a Direct Drive Motor: Experimental Aspects

    NASA Technical Reports Server (NTRS)

    Medina, E.; Akbarzadeh-T, M.-R.; Kim, Y. T.

    1998-01-01

    This paper presents a state feedback adaptive control method for position and velocity control of a direct drive motor. The proposed control scheme allows for integrating heuristic knowledge with mathematical knowledge of a system. It performs well even when mathematical model of the system is poorly understood. The controller consists of an adaptive fuzzy controller and a supervisory controller. The supervisory controller requires only knowledge of the upper bound and lower bound of the system parameters. The fuzzy controller is based on fuzzy basis functions and states of the system. The adaptation law is derived based on the Lyapunov function which ensures that the state of the system asymptotically approaches zero. The proposed controller is applied to a direct drive motor with payload and parameter uncertainty, and the effectiveness is experimentally verified. The real-time performance is compared with simulation results.

  5. 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.

  6. 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.

  7. Adaptive optimization and control using neural networks

    SciTech Connect

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  8. A Framework for Control and Observation in Distributed Environments

    NASA Technical Reports Server (NTRS)

    Smith, Warren

    2001-01-01

    As organizations begin to deploy large computational grids, it has become apparent that systems for observation and control of the resources, services, and applications that make up such grids are needed. Administrators must observe the operation of resources and services to ensure that they are operating correctly and they must control the resources and services to ensure that their operation meets the needs of users. Further, users need to observe the performance of their applications so that this performance can be improved and control how their applications execute in a dynamic grid environment. In this paper we describe our software framework for control and observation of resources, services, and applications that supports such uses and we provide examples of how our framework can be used.

  9. Adaptive Instability Suppression Controls in a Liquid-fueled Combustor

    NASA Technical Reports Server (NTRS)

    Kopasakis, George; DeLaat, John C.

    2002-01-01

    An adaptive control algorithm has been developed for the suppression of combustion thermo-acoustic instabilities. This technique involves modulating the fuel flow in the combustor with a control phase that continuously slides within the stable phase region, in a back and forth motion. The control method is referred to as Adaptive Sliding Phasor Averaged Control (ASPAC). The control method is evaluated against a simplified simulation of the combustion instability. Plans are to validate the control approach against a more physics-based model and an actual experimental combustor rig.

  10. Adaptive hybrid optimal quantum control for imprecisely characterized systems.

    PubMed

    Egger, D J; Wilhelm, F K

    2014-06-20

    Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful. PMID:24996074

  11. Smart Rehabilitation Devices: Part II – Adaptive Motion Control

    PubMed Central

    Dong, Shufang; Lu, Ke-Qian; Sun, J. Q.; Rudolph, Katherine

    2008-01-01

    This article presents a study of adaptive motion control of smart versatile rehabilitation devices using MR fluids. The device provides both isometric and isokinetic strength training and is reconfigurable for several human joints. Adaptive controls are developed to regulate resistance force based on the prescription of the therapist. Special consideration has been given to the human–machine interaction in the adaptive control that can modify the behavior of the device to account for strength gains or muscle fatigue of the human subject. PMID:18548131

  12. Development of a digital adaptive optimal linear regulator flight controller

    NASA Technical Reports Server (NTRS)

    Berry, P.; Kaufman, H.

    1975-01-01

    Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.

  13. Discrete-time adaptive control of robot manipulators

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1989-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.

  14. Disturbance Accommodating Adaptive Control with Application to Wind Turbines

    NASA Technical Reports Server (NTRS)

    Frost, Susan

    2012-01-01

    Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.

  15. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a dual-adaptive feedback control unit for a highly nonlinear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the nonlinear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a dual-adaptive control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  16. Dynamics and Adaptive Control for Stability Recovery of Damaged Aircraft

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan; Krishnakumar, Kalmanje; Kaneshige, John; Nespeca, Pascal

    2006-01-01

    This paper presents a recent study of a damaged generic transport model as part of a NASA research project to investigate adaptive control methods for stability recovery of damaged aircraft operating in off-nominal flight conditions under damage and or failures. Aerodynamic modeling of damage effects is performed using an aerodynamic code to assess changes in the stability and control derivatives of a generic transport aircraft. Certain types of damage such as damage to one of the wings or horizontal stabilizers can cause the aircraft to become asymmetric, thus resulting in a coupling between the longitudinal and lateral motions. Flight dynamics for a general asymmetric aircraft is derived to account for changes in the center of gravity that can compromise the stability of the damaged aircraft. An iterative trim analysis for the translational motion is developed to refine the trim procedure by accounting for the effects of the control surface deflection. A hybrid direct-indirect neural network, adaptive flight control is proposed as an adaptive law for stabilizing the rotational motion of the damaged aircraft. The indirect adaptation is designed to estimate the plant dynamics of the damaged aircraft in conjunction with the direct adaptation that computes the control augmentation. Two approaches are presented 1) an adaptive law derived from the Lyapunov stability theory to ensure that the signals are bounded, and 2) a recursive least-square method for parameter identification. A hardware-in-the-loop simulation is conducted and demonstrates the effectiveness of the direct neural network adaptive flight control in the stability recovery of the damaged aircraft. A preliminary simulation of the hybrid adaptive flight control has been performed and initial data have shown the effectiveness of the proposed hybrid approach. Future work will include further investigations and high-fidelity simulations of the proposed hybrid adaptive Bight control approach.

  17. A Robust Control Design Framework for Substructure Models

    NASA Technical Reports Server (NTRS)

    Lim, Kyong B.

    1994-01-01

    A framework for designing control systems directly from substructure models and uncertainties is proposed. The technique is based on combining a set of substructure robust control problems by an interface stiffness matrix which appears as a constant gain feedback. Variations of uncertainties in the interface stiffness are treated as a parametric uncertainty. It is shown that multivariable robust control can be applied to generate centralized or decentralized controllers that guarantee performance with respect to uncertainties in the interface stiffness, reduced component modes and external disturbances. The technique is particularly suited for large, complex, and weakly coupled flexible structures.

  18. Adaptive fuzzy backstepping control for a class of switched nonlinear systems with actuator faults

    NASA Astrophysics Data System (ADS)

    Hou, Yingxue; Tong, Shaocheng; Li, Yongming

    2016-11-01

    This paper investigates the problem of fault-tolerant control (FTC) for a class of switched nonlinear systems. These systems are under arbitrary switchings and are subject to both lock-in-place and loss-of-effectiveness actuator faults. In the control design, fuzzy logic systems are used to identify the unknown switched nonlinear systems. Under the framework of the backstepping control design, FTC, fuzzy adaptive control and common Lyapunov function stability theory, an adaptive fuzzy control approach is developed. It is proved that the proposed control approach can guarantee that all the signals in the closed-loop switched system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error remains an adjustable neighbourhood of the origin. Two simulation examples are provided to illustrate the effectiveness of the proposed approach.

  19. Adaptive control of a wheelchair-pushing holonomic robot subject to input constraints

    NASA Astrophysics Data System (ADS)

    Methil, Nandagopal S.; Mukherjee, Ranjan

    2008-04-01

    In our earlier work, we proposed a synergistic design and control strategy to enable a holonomic mobile robot transport wheelchair bound residents in long-term-care facilities. Several simplifying assumptions were made and an adaptive control framework was proposed for wheelchair trajectory tracking. We remove some of the limiting assumptions by considering actuator saturation and actuator dynamics in this paper. We modify the adaptive controller and show that asymptotic trajectory tracking can be achieved provided that the reference trajectory does not result in complete loss of control authority. In the absence of control authority, we suspend trajectory tracking to maintain stability and revert to asymptotic trajectory tracking when control authority is regained. Although we focus on an application for long-term-care facilities, the technology being developed will find diverse applications such as autonomous transportation of hazardous materials.

  20. 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.

  1. Adaptive Failure Compensation for Aircraft Flight Control Using Engine Differentials: Regulation

    NASA Technical Reports Server (NTRS)

    Yu, Liu; Xidong, Tang; Gang, Tao; Joshi, Suresh M.

    2005-01-01

    The problem of using engine thrust differentials to compensate for rudder and aileron failures in aircraft flight control is addressed in this paper in a new framework. A nonlinear aircraft model that incorporates engine di erentials in the dynamic equations is employed and linearized to describe the aircraft s longitudinal and lateral motion. In this model two engine thrusts of an aircraft can be adjusted independently so as to provide the control flexibility for rudder or aileron failure compensation. A direct adaptive compensation scheme for asymptotic regulation is developed to handle uncertain actuator failures in the linearized system. A design condition is specified to characterize the system redundancy needed for failure compensation. The adaptive regulation control scheme is applied to the linearized model of a large transport aircraft in which the longitudinal and lateral motions are coupled as the result of using engine thrust differentials. Simulation results are presented to demonstrate the effectiveness of the adaptive compensation scheme.

  2. 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.

  3. Can survival processing enhance story memory? Testing the generalizability of the adaptive memory framework.

    PubMed

    Seamon, John G; Bohn, Justin M; Coddington, Inslee E; Ebling, Maritza C; Grund, Ethan M; Haring, Catherine T; Jang, Sue-Jung; Kim, Daniel; Liong, Christopher; Paley, Frances M; Pang, Luke K; Siddique, Ashik H

    2012-07-01

    Research from the adaptive memory framework shows that thinking about words in terms of their survival value in an incidental learning task enhances their free recall relative to other semantic encoding strategies and intentional learning (Nairne, Pandeirada, & Thompson, 2008). We found similar results. When participants used incidental survival encoding for a list of words (e.g., "Will this object enhance my survival if I were stranded in the grasslands of a foreign land?"), they produced better free recall on a surprise test than did participants who intentionally tried to remember those words (Experiment 1). We also found this survival processing advantage when the words were presented within the context of a survival or neutral story (Experiment 2). However, this advantage did not extent to memory for a story's factual content, regardless of whether the participants were tested by cued recall (Experiment 3) or free recall (Experiments 4-5). Listening to a story for understanding under intentional or incidental learning conditions was just as good as survival processing for remembering story content. The functionalist approach to thinking about memory as an evolutionary adaptation designed to solve reproductive fitness problems provides a different theoretical framework for research, but it is not yet clear if survival processing has general applicability or is effective only for processing discrete stimuli in terms of fitness-relevant scenarios from our past. PMID:22288816

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  7. Adaptive Importance Sampling for Control and Inference

    NASA Astrophysics Data System (ADS)

    Kappen, H. J.; Ruiz, H. C.

    2016-03-01

    Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

  8. Lake eutrophication and environmental change: A viability framework for resilience, vulnerability and adaptive capacity

    NASA Astrophysics Data System (ADS)

    Mathias, Jean-Denis; Rougé, Charles; Deffuant, Guillaume

    2013-04-01

    We present a simple stochastic model of lake eutrophication to demonstrate how the mathematical framework of viability theory fosters operational definitions of resilience, vulnerability and adaptive capacity, and then helps understand which response one should bring to environmental changes. The model represents the phosphorus dynamics, given that high concentrations trigger a regime change from oligotrophic to eutrophic, and causes ecological but also economic losses, for instance from tourism. Phosphorus comes from agricultural inputs upstream of the lake, and we will consider a stochastic input. We consider the system made of both the lake and its upstream region, and explore how to maintain the desirable ecological and economic properties of this system. In the viability framework, we translate these desirable properties into state constraints, then examine how, given the dynamics of the model and the available policy options, the properties can be kept. The set of states for which there exists a policy to keep the properties is called the viability kernel. We extend this framework to both major perturbations and long-term environmental changes. In our model, since the phosphorus inputs and outputs from the lake depend on rainfall, we will focus on extreme rainfall events and long-term changes in the rainfall regime. They can be described as changes in the state of the system, and may displace it outside the viability kernel. Its response can then be described using the concepts of resilience, vulnerability and adaptive capacity. Resilience is the capacity to recover by getting back to the viability kernel where the dynamics keep the system safe, and in this work we assume it to be the first objective of management. Computed for a given trajectory, vulnerability is a measure of the consequence of violating a property. We propose a family of functions from which cost functions and other vulnerability indicators can be derived for any trajectory. There can be

  9. Missile guidance law design using adaptive cerebellar model articulation controller.

    PubMed

    Lin, Chih-Min; Peng, Ya-Fu

    2005-05-01

    An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law.

  10. Adaptive hybrid position/force control of robotic manipulators

    NASA Technical Reports Server (NTRS)

    Pourboghrat, F.

    1987-01-01

    The problem of position and force control for the compliant motion of the manipulators is considered. The external force and the position of the end-effector are related by a second order impedance function. The force control problem is then translated into a position control problem. For that, an adaptive controller is designed to achieve the compliant motion. The design uses the Liapunov's direct method to derive the adaptation law. The stability of the process is guaranteed from the Liapunov's stability theory. The controller does not require the knowledge of the system parameters for the implementation, and hence is easy for applications.

  11. Digital adaptive controllers for VTOL vehicles. Volume 1: Concept evaluation

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.; Pratt, S. G.

    1979-01-01

    A digital self-adaptive flight control system was developed for flight test in the VTOL approach and landing technology (VALT) research aircraft (a modified CH-47 helicopter). The control laws accept commands from an automatic on-board guidance system. The primary objective of the control laws is to provide good command-following with a minimum cross-axis response. Three attitudes and vertical velocity are separately commanded. Adaptation of the control laws is based on information from rate and attitude gyros and a vertical velocity measurement. The final design resulted from a comparison of two different adaptive concepts--one based on explicit parameter estimates from a real-time maximum-likelihood estimation algorithm, the other based on an implicit model reference adaptive system. The two designs were compared on the basis of performance and complexity.

  12. Adaptive Wavefront Calibration and Control for the Gemini Planet Imager

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-02-02

    Quasi-static errors in the science leg and internal AO flexure will be corrected. Wavefront control will adapt to current atmospheric conditions through Fourier modal gain optimization, or the prediction of atmospheric layers with Kalman filtering.

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

    PubMed

    Peng, Jinzhu; Yu, Jie; Wang, Jie

    2014-07-01

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

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

    PubMed Central

    Carmena, Jose M.

    2016-01-01

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

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

    PubMed

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

    2016-04-01

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

  16. To adapt or not to adapt: the question of domain-general cognitive control.

    PubMed

    Kan, Irene P; Teubner-Rhodes, Susan; Drummey, Anna B; Nutile, Lauren; Krupa, Lauren; Novick, Jared M

    2013-12-01

    What do perceptually bistable figures, sentences vulnerable to misinterpretation and the Stroop task have in common? Although seemingly disparate, they all contain elements of conflict or ambiguity. Consequently, in order to monitor a fluctuating percept, reinterpret sentence meaning, or say "blue" when the word RED is printed in blue ink, individuals must regulate attention and engage cognitive control. According to the Conflict Monitoring Theory (Botvinick, Braver, Barch, Carter, & Cohen, 2001), the detection of conflict automatically triggers cognitive control mechanisms, which can enhance resolution of subsequent conflict, namely, "conflict adaptation." If adaptation reflects the recruitment of domain-general processes, then conflict detection in one domain should facilitate conflict resolution in an entirely different domain. We report two novel findings: (i) significant conflict adaptation from a syntactic to a non-syntactic domain and (ii) from a perceptual to a verbal domain, providing strong evidence that adaptation is mediated by domain-general cognitive control. PMID:24103774

  17. A trust region method in adaptive finite element framework for bioluminescence tomography.

    PubMed

    Zhang, Bo; Yang, Xin; Qin, Chenghu; Liu, Dan; Zhu, Shouping; Feng, Jinchao; Sun, Li; Liu, Kai; Han, Dong; Ma, Xibo; Zhang, Xing; Zhong, Jianghong; Li, Xiuli; Yang, Xiang; Tian, Jie

    2010-03-29

    Bioluminescence tomography (BLT) is an effective molecular imaging (MI) modality. Because of the ill-posedness, the inverse problem of BLT is still open. We present a trust region method (TRM) for BLT source reconstruction. The TRM is applied in the source reconstruction procedure of BLT for the first time. The results of both numerical simulations and the experiments of cube phantom and nude mouse draw us to the conclusion that based on the adaptive finite element (AFE) framework, the TRM works in the source reconstruction procedure of BLT. To make our conclusion more reliable, we also compare the performance of the TRM and that of the famous Tikhonov regularization method after only one step of mesh refinement of the AFE framework. The conclusion is that the TRM can get faster and better results after only one mesh refinement step of AFE framework than the Tikhonov regularization method when handling large scale data. In the TRM, all the parameters are fixed, while in the Tikhonov method the regularization parameter needs to be well selected.

  18. An Adaptive Framework for Selecting Environmental Monitoring Protocols to Support Ocean Renewable Energy Development

    PubMed Central

    Shumchenia, Emily J.; Smith, Sarah L.; McCann, Jennifer; Carnevale, Michelle; Fugate, Grover; Kenney, Robert D.; King, John W.; Paton, Peter; Schwartz, Malia; Spaulding, Malcolm; Winiarski, Kristopher J.

    2012-01-01

    Offshore renewable energy developments (OREDs) are projected to become common in the United States over the next two decades. There are both a need and an opportunity to guide efforts to identify and track impacts to the marine ecosystem resulting from these installations. A monitoring framework and standardized protocols that can be applied to multiple types of ORED would streamline scientific study, management, and permitting at these sites. We propose an adaptive and reactive framework based on indicators of the likely changes to the marine ecosystem due to ORED. We developed decision trees to identify suites of impacts at two scales (demonstration and commercial) depending on energy (wind, tidal, and wave), structure (e.g., turbine), and foundation type (e.g., monopile). Impacts were categorized by ecosystem component (benthic habitat and resources, fish and fisheries, avian species, marine mammals, and sea turtles) and monitoring objectives were developed for each. We present a case study at a commercial-scale wind farm and develop a monitoring plan for this development that addresses both local and national environmental concerns. In addition, framework has provided a starting point for identifying global research needs and objectives for understanding of the potential effects of ORED on the marine environment. PMID:23319884

  19. An adaptive framework for selecting environmental monitoring protocols to support ocean renewable energy development.

    PubMed

    Shumchenia, Emily J; Smith, Sarah L; McCann, Jennifer; Carnevale, Michelle; Fugate, Grover; Kenney, Robert D; King, John W; Paton, Peter; Schwartz, Malia; Spaulding, Malcolm; Winiarski, Kristopher J

    2012-01-01

    Offshore renewable energy developments (OREDs) are projected to become common in the United States over the next two decades. There are both a need and an opportunity to guide efforts to identify and track impacts to the marine ecosystem resulting from these installations. A monitoring framework and standardized protocols that can be applied to multiple types of ORED would streamline scientific study, management, and permitting at these sites. We propose an adaptive and reactive framework based on indicators of the likely changes to the marine ecosystem due to ORED. We developed decision trees to identify suites of impacts at two scales (demonstration and commercial) depending on energy (wind, tidal, and wave), structure (e.g., turbine), and foundation type (e.g., monopile). Impacts were categorized by ecosystem component (benthic habitat and resources, fish and fisheries, avian species, marine mammals, and sea turtles) and monitoring objectives were developed for each. We present a case study at a commercial-scale wind farm and develop a monitoring plan for this development that addresses both local and national environmental concerns. In addition, framework has provided a starting point for identifying global research needs and objectives for understanding of the potential effects of ORED on the marine environment. PMID:23319884

  20. An adaptive framework for selecting environmental monitoring protocols to support ocean renewable energy development.

    PubMed

    Shumchenia, Emily J; Smith, Sarah L; McCann, Jennifer; Carnevale, Michelle; Fugate, Grover; Kenney, Robert D; King, John W; Paton, Peter; Schwartz, Malia; Spaulding, Malcolm; Winiarski, Kristopher J

    2012-01-01

    Offshore renewable energy developments (OREDs) are projected to become common in the United States over the next two decades. There are both a need and an opportunity to guide efforts to identify and track impacts to the marine ecosystem resulting from these installations. A monitoring framework and standardized protocols that can be applied to multiple types of ORED would streamline scientific study, management, and permitting at these sites. We propose an adaptive and reactive framework based on indicators of the likely changes to the marine ecosystem due to ORED. We developed decision trees to identify suites of impacts at two scales (demonstration and commercial) depending on energy (wind, tidal, and wave), structure (e.g., turbine), and foundation type (e.g., monopile). Impacts were categorized by ecosystem component (benthic habitat and resources, fish and fisheries, avian species, marine mammals, and sea turtles) and monitoring objectives were developed for each. We present a case study at a commercial-scale wind farm and develop a monitoring plan for this development that addresses both local and national environmental concerns. In addition, framework has provided a starting point for identifying global research needs and objectives for understanding of the potential effects of ORED on the marine environment.

  1. Using the New Scenarios Framework to Inform Climate Change Adaptation Policy in Finland

    NASA Astrophysics Data System (ADS)

    Carter, T. R.

    2013-12-01

    In 2005, Finland was among the first countries in the world to develop a national climate change adaptation strategy (Marttila et al., 2005). This included a characterization of future changes in climate and socioeconomic conditions using scenarios based on the IPCC Special Report on Emissions Scenarios (SRES - IPCC, 2000). Following a government evaluation of the strategy, completion of a national adaptation research programme, and in light of the recent European Union adaptation strategy, the Finnish strategy is now under revision. As part of this revision process, the New Scenario Framework (Moss et al., 2010) is being used to guide the mapping of future conditions in Finland out to the end of the 21st century. Future Finnish climate is being analysed using the CMIP5 climate model simulations (Taylor et al., 2012), including downscaled information based on regional climate model projections in the EURO-CORDEX project (Vautard et al., 2013). All projections are forced by the Representative Concentration Pathways (RCPs - van Vuuren et al., 2011). Socioeconomic scenarios are also being developed by outlining alternative pathways that reflect national social, economic, environmental and planning goals. These are designed according to the Shared Socioeconomic Pathway (SSP) framework of challenges to adaptation and mitigation (Kriegler et al., 2012). Work is in progress to characterize these pathways, mainly qualitatively, for different sectors in Finland. Preliminary results of the conceptual scenario development phase will be presented in this session. These initial ideas will be exchanged with representatives of ministries, regional government and key stakeholder groups. The eventual form and number of scenarios that appear in the revised strategy will be determined following a formal review of the draft document to be prepared in 2014. Future work could include quantification of scenarios, possibly mapping them onto the specific SSP worlds. This would then provide

  2. Borg: an auto-adaptive many-objective evolutionary computing framework.

    PubMed

    Hadka, David; Reed, Patrick

    2013-01-01

    This study introduces the Borg multi-objective evolutionary algorithm (MOEA) for many-objective, multimodal optimization. The Borg MOEA combines ε-dominance, a measure of convergence speed named ε-progress, randomized restarts, and auto-adaptive multioperator recombination into a unified optimization framework. A comparative study on 33 instances of 18 test problems from the DTLZ, WFG, and CEC 2009 test suites demonstrates Borg meets or exceeds six state of the art MOEAs on the majority of the tested problems. The performance for each test problem is evaluated using a 1,000 point Latin hypercube sampling of each algorithm's feasible parameterization space. The statistical performance of every sampled MOEA parameterization is evaluated using 50 replicate random seed trials. The Borg MOEA is not a single algorithm; instead it represents a class of algorithms whose operators are adaptively selected based on the problem. The adaptive discovery of key operators is of particular importance for benchmarking how variation operators enhance search for complex many-objective problems. PMID:22385134

  3. Adaptive control with an expert system based supervisory level. Thesis

    NASA Technical Reports Server (NTRS)

    Sullivan, Gerald A.

    1991-01-01

    Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up

  4. Adaptive Attitude Control of the Crew Launch Vehicle

    NASA Technical Reports Server (NTRS)

    Muse, Jonathan

    2010-01-01

    An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.

  5. A duality framework for stochastic optimal control of complex systems

    SciTech Connect

    Malikopoulos, Andreas A.

    2016-01-01

    In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derive online the optimal control policy in complex systems.

  6. Spatial, Hysteretic, and Adaptive Host-Guest Chemistry in a Metal-Organic Framework with Open Watson-Crick Sites.

    PubMed

    Cai, Hong; Li, Mian; Lin, Xiao-Rong; Chen, Wei; Chen, Guang-Hui; Huang, Xiao-Chun; Li, Dan

    2015-09-01

    Biological and artificial molecules and assemblies capable of supramolecular recognition, especially those with nucleobase pairing, usually rely on autonomous or collective binding to function. Advanced site-specific recognition takes advantage of cooperative spatial effects, as in local folding in protein-DNA binding. Herein, we report a new nucleobase-tagged metal-organic framework (MOF), namely ZnBTCA (BTC=benzene-1,3,5-tricarboxyl, A=adenine), in which the exposed Watson-Crick faces of adenine residues are immobilized periodically on the interior crystalline surface. Systematic control experiments demonstrated the cooperation of the open Watson-Crick sites and spatial effects within the nanopores, and thermodynamic and kinetic studies revealed a hysteretic host-guest interaction attributed to mild chemisorption. We further exploited this behavior for adenine-thymine binding within the constrained pores, and a globally adaptive response of the MOF host was observed.

  7. Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

    NASA Technical Reports Server (NTRS)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  8. Adaptive process control using fuzzy logic and genetic algorithms

    NASA Technical Reports Server (NTRS)

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  9. Adaptive pitch control for load mitigation of wind turbines

    NASA Astrophysics Data System (ADS)

    Yuan, Yuan; Tang, J.

    2015-04-01

    In this research, model reference adaptive control is examined for the pitch control of wind turbines that may suffer from reduced life owing to extreme loads and fatigue when operated under a high wind speed. Specifically, we aim at making a trade-off between the maximum energy captured and the load induced. The adaptive controller is designed to track the optimal generator speed and at the same time to mitigate component loads under turbulent wind field and other uncertainties. The proposed algorithm is tested on the NREL offshore 5-MW baseline wind turbine, and its performance is compared with that those of the gain scheduled proportional integral (GSPI) control and the disturbance accommodating control (DAC). The results show that the blade root flapwise load can be reduced at a slight expense of optimal power output. The generator speed regulation under adaptive controller is better than DAC.

  10. An adaptive learning control system for aircraft

    NASA Technical Reports Server (NTRS)

    Mekel, R.; Nachmias, S.

    1978-01-01

    A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

  11. A Hierarchical Framework for Demand-Side Frequency Control

    SciTech Connect

    Moya, Christian; Zhang, Wei; Lian, Jianming; Kalsi, Karanjit

    2014-06-02

    With large-scale plans to integrate renewable generation, more resources will be needed to compensate for the uncertainty associated with intermittent generation resources. Under such conditions, performing frequency control using only supply-side resources become not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in frequency control to maintain the stability of the system at an acceptable cost. In this paper, a novel hierarchical decentralized framework for frequency based load control is proposed. The framework involves two decision layers. The top decision layer determines the optimal droop gain required from the aggregated load response on each bus using a robust decentralized control approach. The second layer consists of a large number of devices, which switch probabilistically during contingencies so that the aggregated power change matches the desired droop amount according to the updated gains. The proposed framework is based on the classical nonlinear multi-machine power system model, and can deal with timevarying system operating conditions while respecting the physical constraints of individual devices. Realistic simulation results based on a 68-bus system are provided to demonstrate the effectiveness of the proposed strategy.

  12. A tensor-product-kernel framework for multiscale neural activity decoding and control.

    PubMed

    Li, Lin; Brockmeier, Austin J; Choi, John S; Francis, Joseph T; Sanchez, Justin C; Príncipe, José C

    2014-01-01

    Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

  13. Building the framework for climate change adaptation in the urban areas using participatory approach: the Czech Republic experience

    NASA Astrophysics Data System (ADS)

    Emmer, Adam; Hubatová, Marie; Lupač, Miroslav; Pondělíček, Michael; Šafařík, Miroslav; Šilhánková, Vladimíra; Vačkář, David

    2016-04-01

    The Czech Republic has experienced numerous extreme hydrometeorological / climatological events such as floods (significant ones in 1997, 2002, 2010, 2013), droughts (2013, 2015), heat waves (2015) and windstorms (2007) during past decades. These events are generally attributed to the ongoing climate change and caused loss of lives and significant material damages (up to several % of GDP in some years), especially in urban areas. To initiate the adaptation process of urban areas, the main objective was to prepare a framework for creating climate change adaptation strategies of individual cities reflecting physical-geographical and socioeconomical conditions of the Czech Republic. Three pilot cities (Hradec Králové, Žďár nad Sázavou, Dobru\\vska) were used to optimize entire procedure. Two sets of participatory seminars were organised in order to involve all key stakeholders (the city council, department of the environment, department of the crisis management, hydrometeorological institute, local experts, ...) into the process of creation of the adaptation strategy from its early stage. Lesson learned for the framework were related especially to its applicability on a local level, which is largely a matter of the understandability of the concept. Finally, this illustrative and widely applicable framework (so called 'road map to adaptation strategy') includes five steps: (i) analysis of existing strategies and plans on national, regional and local levels; (ii) analysing climate-change related hazards and key vulnerabilities; (iii) identification of adaptation needs, evaluation of existing adaptation capacity and formulation of future adaptation priorities; (iv) identification of limits and barriers for the adaptation (economical, environmental, ...); and (v) selection of specific types of adaptation measures reflecting identified adaptation needs and formulated adaptation priorities. Keywords: climate change adaptation (CCA); urban areas; participatory approach

  14. Investigation of the Multiple Model Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The application was investigated of control theoretic ideas to the design of flight control systems for the F-8 aircraft. The design of an adaptive control system based upon the so-called multiple model adaptive control (MMAC) method is considered. Progress is reported.

  15. Adaptive control of Hammerstein-Wiener nonlinear systems

    NASA Astrophysics Data System (ADS)

    Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong

    2016-07-01

    The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.

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

    PubMed

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

    2008-07-10

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

  17. Decentralized adaptive control of manipulators - Theory, simulation, and experimentation

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1989-01-01

    The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.

  18. Online Parameter Estimation and Adaptive Control of Magnetic Wire Actuators

    NASA Astrophysics Data System (ADS)

    Karve, Harshwardhan

    Cantilevered magnetic wires and fibers can be used as actuators in microfluidic applications. The actuator may be unstable in some range of displacements. Precise position control is required for actuation. The goal of this work is to develop position controllers for cantilevered magnetic wires. A simple exact model knowledge (EMK) controller can be used for position control, but the actuator needs to be modeled accurately for the EMK controller to work. Continuum models have been proposed for magnetic wires in literature. Reduced order models have also been proposed. A one degree of freedom model sufficiently describes the dynamics of a cantilevered wire in the field of one magnet over small displacements. This reduced order model is used to develop the EMK controller here. The EMK controller assumes that model parameters are known accurately. Some model parameters depend on the magnetic field. However, the effect of the magnetic field on the wire is difficult to measure in practice. Stability analysis shows that an inaccurate estimate of the magnetic field introduces parametric perturbations in the closed loop system. This makes the system less robust to disturbances. Therefore, the model parameters need to be estimated accurately for the EMK controller to work. An adaptive observer that can estimate system parameters on-line and reduce parametric perturbations is designed here. The adaptive observer only works if the system is stable. The EMK controller is not guaranteed to stabilize the system under perturbations. Precise tuning of parameters is required to stabilize the system using the EMK controller. Therefore, a controller that stabilizes the system using imprecise model parameters is required for the observer to work as intended. The adaptive observer estimates system states and parameters. These states and parameters are used here to implement an indirect adaptive controller. This indirect controller can stabilize the system using imprecise initial

  19. Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

    NASA Technical Reports Server (NTRS)

    Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don

    2003-01-01

    This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

  20. Identification and dual adaptive control of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  1. Hybrid adaptive ascent flight control for a flexible launch vehicle

    NASA Astrophysics Data System (ADS)

    Lefevre, Brian D.

    For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the

  2. Adaptive measurement control for calorimetric assay

    SciTech Connect

    Glosup, J.G.; Axelrod, M.C.

    1994-10-01

    The performance of a calorimeter is usually evaluated by constructing a Shewhart control chart of its measurement errors for a collection of reference standards. However, Shewhart control charts were developed in a manufacturing setting where observations occur in batches. Additionally, the Shewhart control chart expects the variance of the charted variable to be known or at least well estimated from previous experimentation. For calorimetric assay, observations are collected singly in a time sequence with a (possibly) changing mean, and extensive experimentation to calculate the variance of the measurement errors is seldom feasible. These facts pose problems in constructing a control chart. In this paper, the authors propose using the mean squared successive difference to estimate the variance of measurement errors based solely on prior observations. This procedure reduces or eliminates estimation bias due to a changing mean. However, the use of this estimator requires an adjustment to the definition of the alarm and warning limits for the Shewhart control chart. The authors propose adjusted limits based on an approximate Student`s t-distribution for the measurement errors and discuss the limitations of this approximation. Suggestions for the practical implementation of this method are provided also.

  3. Simulation of a Reconfigurable Adaptive Control Architecture

    NASA Astrophysics Data System (ADS)

    Rapetti, Ryan John

    A set of algorithms and software components are developed to investigate the use of a priori models of damaged aircraft to improve control of similarly damaged aircraft. An addition to Model Predictive Control called state trajectory extrapolation is also developed to deliver good handling qualities in nominal an off-nominal aircraft. System identification algorithms are also used to improve model accuracy after a damage event. Simulations were run to demonstrate the efficacy of the algorithms and software components developed herein. The effect of model order on system identification convergence and performance is also investigated. A feasibility study for flight testing is also conducted. A preliminary hardware prototype was developed, as was the necessary software to integrate the avionics and ground station systems. Simulation results show significant improvement in both tracking and cross-coupling performance when a priori control models are used, and further improvement when identified models are used.

  4. Adaptive control system for pulsed megawatt klystrons

    DOEpatents

    Bolie, Victor W.

    1992-01-01

    The invention provides an arrangement for reducing waveform errors such as errors in phase or amplitude in output pulses produced by pulsed power output devices such as klystrons by generating an error voltage representing the extent of error still present in the trailing edge of the previous output pulse, using the error voltage to provide a stored control voltage, and applying the stored control voltage to the pulsed power output device to limit the extent of error in the leading edge of the next output pulse.

  5. Building a Community Framework for Adaptation to Sea Level Rise and Inundation

    NASA Astrophysics Data System (ADS)

    Culver, M. E.; Schubel, J.; Davidson, M. A.; Haines, J.

    2010-12-01

    Sea level rise and inundation pose a substantial risk to many coastal communities, and the risk is projected to increase because of continued development, changes in the frequency and intensity of inundation events, and acceleration in the rate of sea-level rise. Calls for action at all levels acknowledge that a viable response must engage federal, state and local expertise, perspectives, and resources in a coordinated and collaborative effort. Representatives from a variety of these agencies and organizations have developed a shared framework to help coastal communities structure and facilitate community-wide adaptation processes and to help agencies determine where investments should be made to enable states and local governments to assess impacts and initiate adaptation strategies over the next decade. For sea level rise planning and implementation, the requirements for high-quality data and information are vast and the availability is limited. Participants stressed the importance of data interoperability to ensure that users are able to apply data from a variety of sources and to improve availability and confidence in the data. Participants were able to prioritize the following six categories of data needed to support future sea level rise planning and implementation: - Data to understand land forms and where and how water will flow - Monitoring data and environmental drivers - Consistent sea level rise scenarios and projections across agencies to support local planning - Data to characterize vulnerabilities and impacts of sea level rise - Community characteristics - Legal frameworks and administrative structure. To develop a meaningful and effective sea level rise adaptation plan, state and local planners must understand how the availability, scale, and uncertainty of these types of data will impact new guidelines or adaptation measures. The tools necessary to carry-out the adaptation planning process need to be understood in terms of data requirements

  6. A Computational Framework to Control Verification and Robustness Analysis

    NASA Technical Reports Server (NTRS)

    Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

    2010-01-01

    This paper presents a methodology for evaluating the robustness of a controller based on its ability to satisfy the design requirements. The framework proposed is generic since it allows for high-fidelity models, arbitrary control structures and arbitrary functional dependencies between the requirements and the uncertain parameters. The cornerstone of this contribution is the ability to bound the region of the uncertain parameter space where the degradation in closed-loop performance remains acceptable. The size of this bounding set, whose geometry can be prescribed according to deterministic or probabilistic uncertainty models, is a measure of robustness. The robustness metrics proposed herein are the parametric safety margin, the reliability index, the failure probability and upper bounds to this probability. The performance observed at the control verification setting, where the assumptions and approximations used for control design may no longer hold, will fully determine the proposed control assessment.

  7. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    PubMed Central

    Zhao, Guoliang; Li, Hongxing

    2013-01-01

    This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model. PMID:24453897

  8. Tensor product model transformation based adaptive integral-sliding mode controller: equivalent control method.

    PubMed

    Zhao, Guoliang; Sun, Kaibiao; Li, Hongxing

    2013-01-01

    This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  9. A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing.

    PubMed

    Khan, Suleman; Shiraz, Muhammad; Wahab, Ainuddin Wahid Abdul; Gani, Abdullah; Han, Qi; Rahman, Zulkanain Bin Abdul

    2014-01-01

    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.

  10. A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

    PubMed Central

    Abdul Wahab, Ainuddin Wahid; Han, Qi; Bin Abdul Rahman, Zulkanain

    2014-01-01

    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC. PMID:25097880

  11. Experimental and credentialing capital: an adaptable framework for facilitating science outreach for underrepresented youth.

    PubMed

    Drazan, John F; D'Amato, Anthony R; Winkelman, Max A; Littlejohn, Aaron J; Johnson, Christopher; Ledet, Eric H; Eglash, Ron

    2015-08-01

    Increasing the numbers of black, latino and native youth in STEM careers is both an important way to reduce poverty in low income communities, and a contribution to the diversity of thought and experience that drives STEM research. But underrepresented youth are often alienated from STEM. Two new forms of social capital have been identified that can be combined to create a learning environment in which students and researchers can meet and explore an area of shared interest. Experimental capital refers to the intrinsic motivation that students can develop when they learn inquiry techniques for exploring topics that they feel ownership over. Credentialing capital denotes a shared interest and ability between all parties engaged in the experimental endeavor. These two forms of social capital form an adaptable framework for researchers to use to create effective outreach programs. In this case study sports biomechanics was utilized as the area of shared interest and understanding the slam dunk was used as experimental capital.

  12. Toward university modeling instruction--biology: adapting curricular frameworks from physics to biology.

    PubMed

    Manthey, Seth; Brewe, Eric

    2013-06-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence.

  13. Toward University Modeling Instruction—Biology: Adapting Curricular Frameworks from Physics to Biology

    PubMed Central

    Manthey, Seth; Brewe, Eric

    2013-01-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence. PMID:23737628

  14. Adaptive change in electrically stimulated muscle: a framework for the design of clinical protocols.

    PubMed

    Salmons, Stanley

    2009-12-01

    Adult mammalian skeletal muscles have a remarkable capacity for adapting to increased use. Although this behavior is familiar from the changes brought about by endurance exercise, it is seen to a much greater extent in the response to long-term neuromuscular stimulation. The associated phenomena include a markedly increased resistance to fatigue, and this is the key to several clinical applications. However, a more rational basis is needed for designing regimes of stimulation that are conducive to an optimal outcome. In this review I examine relevant factors, such as the amount, frequency, and duty cycle of stimulation, the influence of force generation, and the animal model. From these considerations a framework emerges for the design of protocols that yield an overall functional profile appropriate to the application. Three contrasting examples illustrate the issues that need to be addressed clinically. PMID:19902542

  15. A Framework for the Development of Context-Adaptable User Interfaces for Ubiquitous Computing Systems

    PubMed Central

    Varela, Gervasio; Paz-Lopez, Alejandro; Becerra, Jose A.; Duro, Richard

    2016-01-01

    This paper addresses the problem of developing user interfaces for Ubiquitous Computing (UC) and Ambient Intelligence (AmI) systems. These kind of systems are expected to provide a natural user experience, considering interaction modalities adapted to the user abilities and preferences and using whatever interaction devices are present in the environment. These interaction devices are not necessarily known at design time. The task is quite complicated due to the variety of devices and technologies, and the diversity of scenarios, and it usually burdens the developer with the need to create many different UIs in order to consider the foreseeable user-environment combinations. Here, we propose an UI abstraction framework for UC and AmI systems that effectively improves the portability of those systems between different environments and for different users. It allows developers to design and implement a single UI capable of being deployed with different devices and modalities regardless the physical location. PMID:27399711

  16. Embedded intelligent adaptive PI controller for an electromechanical system.

    PubMed

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. PMID:27342993

  17. Direct adaptive control of a PUMA 560 industrial robot

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun; Lee, Thomas; Delpech, Michel

    1989-01-01

    The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

  18. Adaptive Identification and Control of Flow-Induced Cavity Oscillations

    NASA Technical Reports Server (NTRS)

    Kegerise, M. A.; Cattafesta, L. N.; Ha, C.

    2002-01-01

    Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

  19. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    NASA Astrophysics Data System (ADS)

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-06-01

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.

  20. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    SciTech Connect

    Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

    2008-06-12

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller.

  1. Adaptive Power Control for Space Communications

    NASA Technical Reports Server (NTRS)

    Thompson, Willie L., II; Israel, David J.

    2008-01-01

    This paper investigates the implementation of power control techniques for crosslinks communications during a rendezvous scenario of the Crew Exploration Vehicle (CEV) and the Lunar Surface Access Module (LSAM). During the rendezvous, NASA requires that the CEV supports two communication links: space-to-ground and crosslink simultaneously. The crosslink will generate excess interference to the space-to-ground link as the distances between the two vehicles decreases, if the output power is fixed and optimized for the worst-case link analysis at the maximum distance range. As a result, power control is required to maintain the optimal power level for the crosslink without interfering with the space-to-ground link. A proof-of-concept will be described and implemented with Goddard Space Flight Center (GSFC) Communications, Standard, and Technology Lab (CSTL).

  2. Adapting Inspection Data for Computer Numerical Control

    NASA Technical Reports Server (NTRS)

    Hutchison, E. E.

    1986-01-01

    Machining time for repetitive tasks reduced. Program converts measurements of stub post locations by coordinate-measuring machine into form used by numerical-control computer. Work time thus reduced by 10 to 15 minutes for each post. Since there are 600 such posts on each injector, time saved per injector is 100 to 150 hours. With modifications this approach applicable to machining of many precise holes on large machine frames and similar objects.

  3. Adaptive neural network motion control of manipulators with experimental evaluations.

    PubMed

    Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910

  4. Adaptive Neural Network Motion Control of Manipulators with Experimental Evaluations

    PubMed Central

    Puga-Guzmán, S.; Moreno-Valenzuela, J.; Santibáñez, V.

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller. PMID:24574910

  5. Adaptive neural network motion control of manipulators with experimental evaluations.

    PubMed

    Puga-Guzmán, S; Moreno-Valenzuela, J; Santibáñez, V

    2014-01-01

    A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounded. The proposed scheme has been experimentally validated in real time. These experimental evaluations were carried in two different mechanical systems: a horizontal two degrees-of-freedom robot and a vertical one degree-of-freedom arm which is affected by the gravitational force. In each one of the two experimental set-ups, the proposed scheme was implemented without and with adaptive neural network compensation. Experimental results confirmed the tracking accuracy of the proposed adaptive neural network-based controller.

  6. Adaptive control experiment with a large flexible structure

    NASA Technical Reports Server (NTRS)

    Ih, Che-Hang Charles; Bayard, David S.; Wang, Shyh Jong; Eldred, Daniel B.

    1988-01-01

    A large space antenna-like ground experiment structure has been developed for conducting research and validation of advanced control technology. A set of proof-of-concept adaptive control experiments for transient and initial deflection regulation with a small set of sensors and actuators were conducted. Very limited knowledge of the plant dynamics and its environment was used in the design of the adaptive controller so that performance could be demonstrated under conditions of gross underlying uncertainties. High performance has been observed under such stringent conditions. These experiments have established a baseline for future studies involving more complex hardware and environmental conditions, and utilizing additional sets of sensors and actuators.

  7. Real-time control system for adaptive resonator

    SciTech Connect

    Flath, L; An, J; Brase, J; Hurd, R; Kartz, M; Sawvel, R; Silva, D

    2000-07-24

    Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

  8. Adaptive Transmission Control Method for Communication-Broadcasting Integrated Services

    NASA Astrophysics Data System (ADS)

    Koto, Hideyuki; Furuya, Hiroki; Nakamura, Hajime

    This paper proposes an adaptive transmission control method for massive and intensive telecommunication traffic generated by communication-broadcasting integrated services. The proposed method adaptively controls data transmissions from viewers depending on the congestion states, so that severe congestion can be effectively avoided. Furthermore, it utilizes the broadcasting channel which is not only scalable, but also reliable for controlling the responses from vast numbers of viewers. The performance of the proposed method is evaluated through experiments on a test bed where approximately one million viewers are emulated. The obtained results quantitatively demonstrate the performance of the proposed method and its effectiveness under massive and intensive traffic conditions.

  9. Adaptive Control of Truss Structures for Gossamer Spacecraft

    NASA Technical Reports Server (NTRS)

    Yang Bong-Jun; Calise, anthony J.; Craig, James I.; Whorton, Mark S.

    2007-01-01

    Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.

  10. A Decentralized Adaptive Approach to Fault Tolerant Flight Control

    NASA Technical Reports Server (NTRS)

    Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor

    2000-01-01

    This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

  11. On Using Exponential Parameter Estimators with an Adaptive Controller

    NASA Technical Reports Server (NTRS)

    Patre, Parag; Joshi, Suresh M.

    2011-01-01

    Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.

  12. Adaptive statistic tracking control based on two-step neural networks with time delays.

    PubMed

    Yi, Yang; Guo, Lei; Wang, Hong

    2009-03-01

    This paper presents a new type of control framework for dynamical stochastic systems, called statistic tracking control (STC). The system considered is general and non-Gaussian and the tracking objective is the statistical information of a given target probability density function (pdf), rather than a deterministic signal. The control aims at making the statistical information of the output pdfs to follow those of a target pdf. For such a control framework, a variable structure adaptive tracking control strategy is first established using two-step neural network models. Following the B-spline neural network approximation to the integrated performance function, the concerned problem is transferred into the tracking of given weights. The dynamic neural network (DNN) is employed to identify the unknown nonlinear dynamics between the control input and the weights related to the integrated function. To achieve the required control objective, an adaptive controller based on the proposed DNN is developed so as to track a reference trajectory. Stability analysis for both the identification and tracking errors is developed via the use of Lyapunov stability criterion. Simulations are given to demonstrate the efficiency of the proposed approach. PMID:19179249

  13. Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation

    NASA Technical Reports Server (NTRS)

    He, Yuning; Lee, Herbert K. H.; Davies, Misty D.

    2012-01-01

    Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.

  14. Adaptive control and orbit determination for elliptical rendezvous

    NASA Astrophysics Data System (ADS)

    Xu, Lijia; Hu, Yong; Jiang, Tiantian

    2016-10-01

    In this paper, we study the control and orbit determination problems for elliptical rendezvous. Autonomous rendezvous is achieved by the proposed adaptive control based on the measurements of relative position and velocity between the chaser and target spacecraft. Moreover, the target orbital elements can be estimated during the rendezvous process. Finally, the effectiveness of the method is illustrated by simulations.

  15. Study on rule-based adaptive fuzzy excitation control technology

    NASA Astrophysics Data System (ADS)

    Zhao, Hui; Wang, Hong-jun; Liu, Lu-yuan; Yue, You-jun

    2008-10-01

    Power system is a kind of typical non-linear system, it is hard to achieve excellent control performance with conventional PID controller under different operating conditions. Fuzzy parameter adaptive PID exciting controller is very efficient to overcome the influence of tiny disturbances, but the performance of the control system will be worsened when operating conditions of the system change greatly or larger disturbances occur. To solve this problem, this article presents a rule adaptive fuzzy control scheme for synchronous generator exciting system. In this scheme the control rule adaptation is implemented by regulating the value of parameter di under the given proportional divisors K1, K2 and K3 of fuzzy sets Ai and Bi. This rule adaptive mechanism is constituted by two groups of original rules about the self-generation and self-correction of the control rule. Using two groups of rules, the control rule activated by status 1 and 2 in figure 2 system can be regulated automatically and simultaneously at the time instant k. The results from both theoretical analysis and simulation show that the presented scheme is effective and feasible and possesses good performance.

  16. Climate change impact and adaptation assessment on food consumption utilizing a new scenario framework.

    PubMed

    Hasegawa, Tomoko; Fujimori, Shinichiro; Shin, Yonghee; Takahashi, Kiyoshi; Masui, Toshihiko; Tanaka, Akemi

    2014-01-01

    We assessed the impacts of climate change and agricultural autonomous adaptation measures (changes in crop variety and planting dates) on food consumption and risk of hunger considering uncertainties in socioeconomic and climate conditions by using a new scenario framework. We combined a global computable general equilibrium model and a crop model (M-GAEZ), and estimated the impacts through 2050 based on future assumptions of socioeconomic and climate conditions. We used three Shared Socioeconomic Pathways as future population and gross domestic products, four Representative Concentration Pathways as a greenhouse gas emissions constraint, and eight General Circulation Models to estimate climate conditions. We found that (i) the adaptation measures are expected to significantly lower the risk of hunger resulting from climate change under various socioeconomic and climate conditions. (ii) population and economic development had a greater impact than climate conditions for risk of hunger at least throughout 2050, but climate change was projected to have notable impacts, even in the strong emission mitigation scenarios. (iii) The impact on hunger risk varied across regions because levels of calorie intake, climate change impacts and land scarcity varied by region.

  17. Comparability of naturalistic and controlled observation assessment of adaptive behavior.

    PubMed

    Millham, J; Chilcutt, J; Atkinson, B L

    1978-07-01

    The comparability of retrospective naturalistic and controlled observation assessment of adaptive behavior was evaluated. The number, degree, and direction of discrepancies were evaluated with respect to level of retardation of the client, rater differences, behavior domain sampled, and prior observational base for the ratings. Generally poor comparability between the procedures was found and questions were raised concerning the types of generalizability that can be made from adaptive behavior assessment obtained under the two procedures.

  18. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    NASA Technical Reports Server (NTRS)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  19. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures was studied. Lattice filters are used widely in the areas of speech and signal processing. Herein, they are used to identify the structural dynamics model of the flexible structures. This identified model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures control is engaged. This type of validation scheme prevents instability when the overall loop is closed. The results obtained from simulation were compared to those obtained from experiments. In this regard, the flexible beam and grid apparatus at the Aerospace Control Research Lab (ACRL) of NASA Langley Research Center were used as the principal candidates for carrying out the above tasks. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods.

  20. Automatic carrier landing system for V/STOL aircraft using L1 adaptive and optimal control

    NASA Astrophysics Data System (ADS)

    Hariharapura Ramesh, Shashank

    This thesis presents a framework for developing automatic carrier landing systems for aircraft with vertical or short take-off and landing capability using two different control strategies---gain-scheduled linear optimal control, and L1 adaptive control. The carrier landing sequence of V/STOL aircraft involves large variations in dynamic pressure and aerodynamic coefficients arising because of the transition from aerodynamic-supported to jet-borne flight, descent to the touchdown altitude, and turns performed to align with the runway. Consequently, the dynamics of the aircraft exhibit a highly non-linear dynamical behavior with variations in flight conditions prior to touchdown. Therefore, the implication is the need for non-linear control techniques to achieve automatic landing. Gain-scheduling has been one of the most widely employed techniques for control of aircraft, which involves designing linear controllers for numerous trimmed flight conditions, and interpolating them to achieve a global non-linear control. Adaptive control technique, on the other hand, eliminates the need to schedule the controller parameters as they adapt to changing flight conditions.

  1. Adapting End Host Congestion Control for Mobility

    NASA Technical Reports Server (NTRS)

    Eddy, Wesley M.; Swami, Yogesh P.

    2005-01-01

    Network layer mobility allows transport protocols to maintain connection state, despite changes in a node's physical location and point of network connectivity. However, some congestion-controlled transport protocols are not designed to deal with these rapid and potentially significant path changes. In this paper we demonstrate several distinct problems that mobility-induced path changes can create for TCP performance. Our premise is that mobility events indicate path changes that require re-initialization of congestion control state at both connection end points. We present the application of this idea to TCP in the form of a simple solution (the Lightweight Mobility Detection and Response algorithm, that has been proposed in the IETF), and examine its effectiveness. In general, we find that the deficiencies presented are both relatively easily and painlessly fixed using this solution. We also find that this solution has the counter-intuitive property of being both more friendly to competing traffic, and simultaneously more aggressive in utilizing newly available capacity than unmodified TCP.

  2. Adaptive mass expulsion attitude control system

    NASA Technical Reports Server (NTRS)

    Rodden, John J. (Inventor); Stevens, Homer D. (Inventor); Carrou, Stephane (Inventor)

    2001-01-01

    An attitude control system and method operative with a thruster controls the attitude of a vehicle carrying the thruster, wherein the thruster has a valve enabling the formation of pulses of expelled gas from a source of compressed gas. Data of the attitude of the vehicle is gathered, wherein the vehicle is located within a force field tending to orient the vehicle in a first attitude different from a desired attitude. The attitude data is evaluated to determine a pattern of values of attitude of the vehicle in response to the gas pulses of the thruster and in response to the force field. The system and the method maintain the attitude within a predetermined band of values of attitude which includes the desired attitude. Computation circuitry establishes an optimal duration of each of the gas pulses based on the pattern of values of attitude, the optimal duration providing for a minimal number of opening and closure operations of the valve. The thruster is operated to provide gas pulses having the optimal duration.

  3. Panaceas, uncertainty, and the robust control framework in sustainability science

    PubMed Central

    Anderies, John M.; Rodriguez, Armando A.; Janssen, Marco A.; Cifdaloz, Oguzhan

    2007-01-01

    A critical challenge faced by sustainability science is to develop strategies to cope with highly uncertain social and ecological dynamics. This article explores the use of the robust control framework toward this end. After briefly outlining the robust control framework, we apply it to the traditional Gordon–Schaefer fishery model to explore fundamental performance–robustness and robustness–vulnerability trade-offs in natural resource management. We find that the classic optimal control policy can be very sensitive to parametric uncertainty. By exploring a large class of alternative strategies, we show that there are no panaceas: even mild robustness properties are difficult to achieve, and increasing robustness to some parameters (e.g., biological parameters) results in decreased robustness with respect to others (e.g., economic parameters). On the basis of this example, we extract some broader themes for better management of resources under uncertainty and for sustainability science in general. Specifically, we focus attention on the importance of a continual learning process and the use of robust control to inform this process. PMID:17881574

  4. Measuring the Impact of a Moving Target: Towards a Dynamic Framework for Evaluating Collaborative Adaptive Interactive Technologies

    PubMed Central

    Witteman, Holly; Bender, Jacqueline L; Urowitz, Sara; Wiljer, David; Jadad, Alejandro R

    2009-01-01

    Background Website evaluation is a key issue for researchers, organizations, and others responsible for designing, maintaining, endorsing, approving, and/or assessing the use and impact of interventions designed to influence health and health services. Traditionally, these evaluations have included elements such as content credibility, interface usability, and overall design aesthetics. With the emergence of collaborative, adaptive, and interactive ("Web 2.0") technologies such as wikis and other forms of social networking applications, these metrics may no longer be sufficient to adequately assess the quality, use or impact of a health website. Collaborative, adaptive, interactive applications support different ways for people to interact with health information on the Web, including the potential for increased user participation in the design, creation, and maintenance of such sites. Objective We propose a framework that addresses how to evaluate collaborative, adaptive, and interactive applications. Methods In this paper, we conducted a comprehensive review of a variety of databases using terminology related to this area. Results We present a review of evaluation frameworks and also propose a framework that incorporates collaborative, adaptive, and interactive technologies, grounded in evaluation theory. Conclusion This framework can be applied by researchers who wish to compare Web-based interventions, non-profit organizations, and clinical groups who aim to provide health information and support about a particular health concern via the Web, and decisions about funding grants by agencies interested in the role of social networks and collaborative, adaptive, and interactive technologies technologies to improve health and the health system. PMID:19632973

  5. Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

    PubMed

    Zhang, Yanjun; Tao, Gang; Chen, Mou

    2016-09-01

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

  6. Neuro adaptive control for aerospace and distributed systems

    NASA Astrophysics Data System (ADS)

    Das, Abhijit

    Nonlinear and adaptive control is generally considered one of the most effective techniques for stabilizing complex nonlinear systems, where linear control techniques may fail completely. Thousands of research papers are published on either theory or applications of nonlinear and adaptive control. But often one obvious question arises how to implement these techniques in real life model? The best answer that one can think of is to develop simple nonlinear control laws which are easy to implement. Moreover for controlling multi-agent systems, it is often required to distribute the control laws based on limited information available among the agents. This research provides some of these issues in the following way. a) Autopilot design for Aerospace systems: this research developes adaptive backstepping and dynamic inversion methods with internal dynamics stabilization for the quadrotor. Quadrotor helicopter models usually show two main characteristics. First, strong coupling among the system states and second, under-actuation where many states are to be controlled with few control inputs. Due to these unique characteristics, the design of stabilizing control inputs is always challenging for quadrotor models. To confront these problems, first, a dynamic inversion technique with zero dynamics stabilization loop is introduced to a practical quadrotor model, second, an adaptive-backstepping technique is developed to a lagrangian quadrotor model. The stabilizing control laws for both of these techniques are developed using on Lyapunov based method; and b) Coordination of multi-agent systems: coordination among multiple agents is generally done based on balanced or bi-directed communication graph models. If the agents are nonlinear and passive then for a balanced graph model synchronization is possible. But, for other than balanced and bi-directed graph models, it is difficult to synchronize nonlinear systems. Moreover, the performance of synchronization is normally

  7. Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient Control

    NASA Technical Reports Server (NTRS)

    Kopasakis, George

    1997-01-01

    Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.

  8. 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.

  9. Adaptive control of large space structures using recursive lattice filters

    NASA Technical Reports Server (NTRS)

    Sundararajan, N.; Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.

  10. Autonomous and Adaptive Voltage Control using Multiple Distributed Energy Resources

    SciTech Connect

    Li, Huijuan; Li, Fangxing; Xu, Yan; Rizy, D Tom

    2012-01-01

    Voltage regulation using distributed energy resources (DE) or distributed generators (DG) with power electronics interfaces and logic control has drawn increasing interests. This paper addresses the challenges of controlling multiple DEs to regulate voltages in distribution systems using an autonomous and adaptive control approach. Theoretical analysis shows that there exists a corresponding formulation of the dynamic control parameters with multiple DEs. Hence, the proposed control method is theoretically solid. Simulation results confirm that this method is capable of satisfying the fast response requirement for operational use without causing oscillation or inefficiency. This method is autonomous based on local information and the other DEs input without the instructions from any control center, is widely adaptive to variable power system operational situations, and has a high tolerance to data shortage of systems parameter. Hence, it is suitable for broad utility application

  11. An adaptable Boolean net trainable to control a computing robot

    SciTech Connect

    Lauria, F. E.; Prevete, R.; Milo, M.; Visco, S.

    1999-03-22

    We discuss a method to implement in a Boolean neural network a Hebbian rule so to obtain an adaptable universal control system. We start by presenting both the Boolean neural net and the Hebbian rule we have considered. Then we discuss, first, the problems arising when the latter is naively implemented in a Boolean neural net, second, the method consenting us to overcome them and the ensuing adaptable Boolean neural net paradigm. Next, we present the adaptable Boolean neural net as an intelligent control system, actually controlling a writing robot, and discuss how to train it in the execution of the elementary arithmetic operations on operands represented by numerals with an arbitrary number of digits.

  12. Parallel computation of geometry control in adaptive truss structures

    NASA Technical Reports Server (NTRS)

    Ramesh, A. V.; Utku, S.; Wada, B. K.

    1992-01-01

    The fast computation of geometry control in adaptive truss structures involves two distinct parts: the efficient integration of the inverse kinematic differential equations that govern the geometry control and the fast computation of the Jacobian, which appears on the right-hand-side of the inverse kinematic equations. This paper present an efficient parallel implementation of the Jacobian computation on an MIMD machine. Large speedup from the parallel implementation is obtained, which reduces the Jacobian computation to an O(M-squared/n) procedure on an n-processor machine, where M is the number of members in the adaptive truss. The parallel algorithm given here is a good candidate for on-line geometry control of adaptive structures using attached processors.

  13. A discrete-time adaptive control scheme for robot manipulators

    NASA Technical Reports Server (NTRS)

    Tarokh, M.

    1990-01-01

    A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

  14. Adaptive bioinspired landmark identification for navigation control

    NASA Astrophysics Data System (ADS)

    Arena, Paolo; Cruse, Holk; Fortuna, Luigi; Lombardo, Davide; Patané, Luca; Rapisarda, Rosa

    2007-05-01

    In this paper a new methodology for landmark navigation will be introduced. Either for animals or for artificial agents, the whole problem of landmark navigation can be divided into two parts: first, the agent has to recognize, from the dynamic environment, space invariant objects which can be considered as suitable landmarks for driving the motion towards a goal position; second, it has to use the information on the landmarks to effectively navigate within the environment. Here, the problem of determining landmarks has been addressed by processing the external information through a spiking network with dynamic synapses plastically tuned by an STDP algorithm. The learning processes establish correlations between the incoming stimuli, allowing the system to extract from the scenario important features which can play the role of landmarks. Once established the landmarks, the agent acquires geometric relationships between them and the goal position. This process defines the parameters of a recurrent neural network (RNN). This in turn drives the agent navigation, filtering the information about landmarks given within an absolute reference system (e.g the North). When the absolute reference is not available, a safety mechanism acts to control the motion maintaining a correct heading. Simulation results showed the potentiality of the proposed architecture: this is able to drive an agent towards the desired position in presence of stimuli subject to noise and also in the case of partially obscured landmarks.

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

    SciTech Connect

    Kurt Derr; Milos Manic

    2013-11-01

    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 dispersion 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.

  16. Increasing autonomy of precision spacecraft using neural network adaptive control

    NASA Astrophysics Data System (ADS)

    Denoyer, Keith K.; Ninneman, R. Rory

    1999-01-01

    In recent years, there has been a significant interest in the use of adaptive methods for controlling structures in high precision aerospace applications. This is because adaptive methods offer the potential to autonomously adjust to system characteristics different from those modeled or seen in qualification testing. This is especially true of spacecraft, which are generally tested in a 1-g environment. Despite extensive research, it remains extremely difficult to predict on-orbit 0-g behavior. In addition, system dynamics often tend to be time varying. This can take the form of slow changes due to degradation of materials and aging of the spacecraft or sudden failures such as the loss of a sensor or actuator. These events become increasingly likely as spacecraft become more and more complex. By decreasing modeling and testing requirements, lowering operations and maintenance activities that require human intervention, and increasing reliability, adaptive methods have the potential to significantly reduce cost and increase performance of these systems. One class of adaptive control methods are those which utilize artificial neural networks. The use of neural networks has become increasingly mature in a number of areas such as image processing and speech recognition. However, despite a number of publications on the subject, very few instances exist where neural networks have actually been used in control and in particular, structural control applications. The United States Air Force Research Laboratory (AFRL) is currently engaged in advancing adaptive neural control technologies for application to precision space systems. This paper gives an overview of several past and current ground and space based adaptive neural control experiments.

  17. Active Attenuation of Acoustic Noise Using Adaptive Armax Control.

    NASA Astrophysics Data System (ADS)

    Swanson, David Carl

    An adaptive auxiliary input autoregressive moving average (ARMAX) control system using the recursive least -squares lattice for system identification is developed for active control of dynamic systems. The closed-loop adaptive ARMAX control system is applied to active acoustic noise reduction in three-dimensional spaces. The structure of the ARMAX system is compared to that for duct cancellation systems, model-reference control systems, and the general field solution and is seen as a reasonable approach for active field control in the general case. The ARMAX system is derived for multiple inputs and outputs where the measured outputs are to be driven to desired waveforms with least -squares error using a multi-channel ARMAX lattice for recursive system identification. A significant reduction in complexity is obtained by neglecting the ARMAX zeros for the special case of active attenuation of non-dispersive acoustic waves. It is shown that using the least-squares lattice requires fewer multiplies, divides, additions, and subtractions than the recursive least-squares algorithm which is based on the matrix inversion lemma. Computational complexity is seen as an important issue in the application of adaptive ARMAX systems to active field control because the system must control relatively higher numbers of modes and frequencies in real time than are seen in industrial process plants for which the adaptive ARMAX systems were first developed using recursive least squares. Convergence requirements using the lattice system identification algorithm are the same as that for the recursive least squares algorithm in adaptive ARMAX system and are verified in numerical simulations using known ARMAX parameters. A real-time simulation of active attenuation of acoustic noise is presented using the blade-excited harmonics from a small axial flow fan. The adaptive ARMAX controller provides active attenuation for correlated spectral peaks but not for uncorrelated noise from turbulence

  18. Adaptive mechanism-based congestion control for networked systems

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  19. A duality framework for stochastic optimal control of complex systems

    DOE PAGES

    Malikopoulos, Andreas A.

    2016-01-01

    In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less

  20. Adaptive control system having hedge unit and related apparatus and methods

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

    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.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Tryfonidis, Michail

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

  3. Distributed Framework for Dynamic Telescope and Instrument Control

    NASA Technical Reports Server (NTRS)

    Ames, Troy J.; Case, Lynne

    2002-01-01

    Traditionally, instrument command and control systems have been developed specifically for a single instrument. Such solutions are frequently expensive and are inflexible to support the next instrument development effort. NASA Goddard Space Flight Center is developing an extensible framework, known as Instrument Remote Control (IRC) that applies to any kind of instrument that can be controlled by a computer. IRC combines the platform independent processing capabilities of Java with the power of the Extensible Markup Language (XML). A key aspect of the architecture is software that is driven by an instrument description, written using the Instrument Markup Language (IML). IML is an XML dialect used to describe graphical user interfaces to control and monitor the instrument, command sets and command formats, data streams, communication mechanisms, and data processing algorithms. The IRC framework provides the ability to communicate to components anywhere on a network using the JXTA protocol for dynamic discovery of distributed components. JXTA (see httD://www.jxta.org,) is a generalized protocol that allows any devices connected by a network to communicate in a peer-to-peer manner. IRC uses JXTA to advertise a device's IML and discover devices of interest on the network. Devices can join or leave the network and thus join or leave the instrument control environment of IRC. Currently, several astronomical instruments are working with the IRC development team to develop custom components for IRC to control their instruments. These instruments include: High resolution Airborne Wideband Camera (HAWC), a first light instrument for the Stratospheric Observatory for Infrared Astronomy (SOFIA); Submillimeter And Far Infrared Experiment (SAFIRE), a Principal Investigator instrument for SOFIA; and Fabry-Perot Interferometer Bolometer Research Experiment (FIBRE), a prototype of the SAFIRE instrument, used at the Caltech Submillimeter Observatory (CSO). Most recently, we have

  4. Fault-Tolerant Trajectory Tracking of Unmanned Aerial Vehicles Using Immunity-Based Model Reference Adaptive Control

    NASA Astrophysics Data System (ADS)

    Wilburn, Brenton K.

    This dissertation presents the design, development, and simulation testing of an adaptive trajectory tracking algorithm capable of compensating for various aircraft subsystem failures and upset conditions. A comprehensive adaptive control framework, here within referred to as the immune model reference adaptive control (IMRAC) algorithm, is developed by synergistically merging core concepts from the biologically- inspired artificial immune system (AIS) paradigm with more traditional optimal and adaptive control techniques. In particular, a model reference adaptive control (MRAC) algorithm is enhanced with the detection and learning capabilities of a novel, artificial neural network augmented AIS scheme. With the given modifications, the MRAC scheme is capable of detecting and identifying a given failure or upset condition, learning how to adapt to the problem, responding in a manner specific to the given failure condition, and retaining the learning parameters for quicker adaptation to subsequent failures of the same nature. The IMRAC algorithm developed in this dissertation is applicable to a wide range of control problems. However, the proposed methodology is demonstrated in simulation for an unmanned aerial vehicle. The results presented show that the IMRAC algorithm is an effective and valuable extension to traditional optimal and adaptive control techniques. The implementation of this methodology can potentially have significant impacts on the operational safety of many complex systems.

  5. A framework for extreme-event control in wastewater treatment.

    PubMed

    Rosen, C; Larsson, M; Jeppsson, U; Yuan, Z

    2002-01-01

    In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers. The methodology is illustrated in a simulation study.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Feng; Duan, Guangren

    2013-05-01

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

  7. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    NASA Technical Reports Server (NTRS)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  8. The design of digital-adaptive controllers for VTOL aircraft

    NASA Technical Reports Server (NTRS)

    Stengel, R. F.; Broussard, J. R.; Berry, P. W.

    1976-01-01

    Design procedures for VTOL automatic control systems have been developed and are presented. Using linear-optimal estimation and control techniques as a starting point, digital-adaptive control laws have been designed for the VALT Research Aircraft, a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. These control laws are designed to interface with velocity-command and attitude-command guidance logic, which could be used in short-haul VTOL operations. Developments reported here include new algorithms for designing non-zero-set-point digital regulators, design procedures for rate-limited systems, and algorithms for dynamic control trim setting.

  9. Model-free adaptive control of advanced power plants

    SciTech Connect

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  10. Ground adaptive standing controller for a powered transfemoral prosthesis.

    PubMed

    Lawson, Brian E; Varol, Huseyin Atakan; Goldfarb, Michael

    2011-01-01

    The scope of this work is the design and verification of a new standing controller for a powered knee and ankle prosthesis. The controller is based upon a finite-state impedance control approach previously developed by the authors. The controller provides a comprehensive standing behavior that incorporates ground adaptation for unlevel terrain. An amputee subject tested the controller with a powered prosthesis for a variety of standing conditions. Results indicate that the powered prosthesis can estimate the ground slope within ±1 degree over a range of ±15 degrees, and that it can provide appropriate joint impedances for standing on slopes within this range.

  11. Adaptive-Control Experiments On A Large Flexible Structure

    NASA Technical Reports Server (NTRS)

    Ih, Che-Hang C.; Bayard, David S.; Wang, Shyh J.; Eldred, Daniel B.

    1990-01-01

    Antennalike flexible structure built for research in advanced technology including suppression of vibrations and control of initial deflections. Structure instrumented with sensors and actuators connected to digital electronic control system, programmed with control algorithms to be tested. Particular attention in this research focused on direct model-reference adaptive-control algorithm based on command generator tracker theory. Built to exhibit multiple vibrational modes, low modal frequencies, and low structural damping. Made three-dimensional so complicated interactions among components of structure and control system investigated.

  12. 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.

  13. Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems.

    PubMed

    Vrabie, Draguna; Lewis, Frank

    2009-04-01

    In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided.

  14. Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems.

    PubMed

    Vrabie, Draguna; Lewis, Frank

    2009-04-01

    In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided. PMID:19362449

  15. Feedback control as a framework for understanding tradeoffs in biology.

    PubMed

    Cowan, Noah J; Ankarali, Mert M; Dyhr, Jonathan P; Madhav, Manu S; Roth, Eatai; Sefati, Shahin; Sponberg, Simon; Stamper, Sarah A; Fortune, Eric S; Daniel, Thomas L

    2014-07-01

    Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system. PMID:24893678

  16. Adaptive support vector regression for UAV flight control.

    PubMed

    Shin, Jongho; Jin Kim, H; Kim, Youdan

    2011-01-01

    This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model.

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

    NASA Technical Reports Server (NTRS)

    Rodriguez, Guillermo (Editor)

    1990-01-01

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

  18. Experiments in Nonlinear Adaptive Control of Multi-Manipulator, Free-Flying Space Robots

    NASA Technical Reports Server (NTRS)

    Chen, Vincent Wei-Kang

    1992-01-01

    Sophisticated robots can greatly enhance the role of humans in space by relieving astronauts of low level, tedious assembly and maintenance chores and allowing them to concentrate on higher level tasks. Robots and astronauts can work together efficiently, as a team; but the robot must be capable of accomplishing complex operations and yet be easy to use. Multiple cooperating manipulators are essential to dexterity and can broaden greatly the types of activities the robot can achieve; adding adaptive control can ease greatly robot usage by allowing the robot to change its own controller actions, without human intervention, in response to changes in its environment. Previous work in the Aerospace Robotics Laboratory (ARL) have shown the usefulness of a space robot with cooperating manipulators. The research presented in this dissertation extends that work by adding adaptive control. To help achieve this high level of robot sophistication, this research made several advances to the field of nonlinear adaptive control of robotic systems. A nonlinear adaptive control algorithm developed originally for control of robots, but requiring joint positions as inputs, was extended here to handle the much more general case of manipulator endpoint-position commands. A new system modelling technique, called system concatenation was developed to simplify the generation of a system model for complicated systems, such as a free-flying multiple-manipulator robot system. Finally, the task-space concept was introduced wherein the operator's inputs specify only the robot's task. The robot's subsequent autonomous performance of each task still involves, of course, endpoint positions and joint configurations as subsets. The combination of these developments resulted in a new adaptive control framework that is capable of continuously providing full adaptation capability to the complex space-robot system in all modes of operation. The new adaptive control algorithm easily handles free

  19. ARC Control Tower: A flexible generic distributed job management framework

    NASA Astrophysics Data System (ADS)

    Nilsen, J. K.; Cameron, D.; Filipčič, A.

    2015-12-01

    While current grid middleware implementations are quite advanced in terms of connecting jobs to resources, their client tools are generally quite minimal and features for managing large sets of jobs are left to the user to implement. The ARC Control Tower (aCT) is a very flexible job management framework that can be run on anything from a single users laptop to a multi-server distributed setup. aCT was originally designed to enable ATLAS jobs to be submitted to the ARC CE. However, with the recent redesign of aCT where the ATLAS specific elements are clearly separated from the ARC job management parts, the control tower can now easily be reused as a flexible generic distributed job manager for other communities. This paper will give a detailed explanation how aCT works as a job management framework and go through the steps needed to create a simple job manager using aCT and show that it can easily manage thousands of jobs.

  20. Microgravity isolation system design: A modern control synthesis framework

    NASA Technical Reports Server (NTRS)

    Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

    1994-01-01

    Manned orbiters will require active vibration isolation for acceleration-sensitive microgravity science experiments. Since umbilicals are highly desirable or even indispensable for many experiments, and since their presence greatly affects the complexity of the isolation problem, they should be considered in control synthesis. A general framework is presented for applying extended H2 synthesis methods to the three-dimensional microgravity isolation problem. The methodology integrates control and state frequency weighting and input and output disturbance accommodation techniques into the basic H2 synthesis approach. The various system models needed for design and analysis are also presented. The paper concludes with a discussion of a general design philosophy for the microgravity vibration isolation problem.

  1. Microgravity isolation system design: A modern control synthesis framework

    NASA Technical Reports Server (NTRS)

    Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

    1994-01-01

    Manned orbiters will require active vibration isolation for acceleration-sensitive microgravity science experiments. Since umbilicals are highly desirable or even indispensable for many experiments, and since their presence greatly affects the complexity of the isolation problem, they should be considered in control synthesis. In this paper a general framework is presented for applying extended H2 synthesis methods to the three-dimensional microgravity isolation problem. The methodology integrates control and state frequency weighting and input and output disturbance accommodation techniques into the basic H2 synthesis approach. The various system models needed for design and analysis are also presented. The paper concludes with a discussion of a general design philosophy for the microgravity vibration isolation problem.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  3. Adaptive backstepping slide mode control of pneumatic position servo system

    NASA Astrophysics Data System (ADS)

    Ren, Haipeng; Fan, Juntao

    2016-06-01

    With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.

  4. A Conditional Exposure Control Method for Multidimensional Adaptive Testing

    ERIC Educational Resources Information Center

    Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A.

    2009-01-01

    In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…

  5. Controlling Item Exposure Rates in a Realistic Adaptive Testing Paradigm.

    ERIC Educational Resources Information Center

    Stocking, Martha L.

    In the context of paper and pencil testing, the frequency of the exposure of items is usually controlled through policies that regulate both the reuse of test forms and the frequency with which a candidate may retake the test. In the context of computerized adaptive testing, where item pools are large and expensive to produce and testing can be on…

  6. Adaptive Insecure Attachment and Resource Control Strategies during Middle Childhood

    ERIC Educational Resources Information Center

    Chen, Bin-Bin; Chang, Lei

    2012-01-01

    By integrating the life history theory of attachment with resource control theory, the current study examines the hypothesis that insecure attachment styles reorganized in middle childhood are alternative adaptive strategies used to prepare for upcoming competition with the peer group. A sample of 654 children in the second through seventh grades…

  7. Rapid inversion of velocity map images for adaptive femtosecond control

    NASA Astrophysics Data System (ADS)

    Rallis, C.; Andrews, P.; Averin, R.; Jochim, B.; Gregerson, N.; Wells, E.; Zohrabi, M.; de, S.; Gaire, B.; Carnes, K. D.; Ben-Itzhak, I.; Bergues, B.; Kling, M. F.

    2011-05-01

    We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. We report techniques developed to utilize three dimensional momentum information as feedback in adaptive femtosecond control of molecular systems. Velocity map imaging of the dissociating ions following interaction with an intense ultrafast laser pulse provides raw data. In order to recover momentum information, however, the two-dimensional image must be inverted to reconstruct the three-dimensional photofragment distribution. Using a variation of the onion-peeling technique, we invert 1054 × 1040 pixel images in under 1 second. This rapid inversion allows a slice of the momentum distribution to be used as feedback in a closed-loop adaptive control scheme. This work supported by National Science Foundation award PHY-0969687 and the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Science, Office of Science, US Department of Energy.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  9. Opportunistic management of estuaries under climate change: A new adaptive decision-making framework and its practical application.

    PubMed

    Peirson, William; Davey, Erica; Jones, Alan; Hadwen, Wade; Bishop, Keith; Beger, Maria; Capon, Samantha; Fairweather, Peter; Creese, Bob; Smith, Timothy F; Gray, Leigh; Tomlinson, Rodger

    2015-11-01

    Ongoing coastal development and the prospect of severe climate change impacts present pressing estuary management and governance challenges. Robust approaches must recognise the intertwined social and ecological vulnerabilities of estuaries. Here, a new governance and management framework is proposed that recognises the integrated social-ecological systems of estuaries so as to permit transformative adaptation to climate change within these systems. The framework lists stakeholders and identifies estuarine uses and values. Goals are categorised that are specific to ecosystems, private property, public infrastructure, and human communities. Systematic adaptation management strategies are proposed with conceptual examples and associated governance approaches. Contrasting case studies are used to illustrate the practical application of these ideas. The framework will assist estuary managers worldwide to achieve their goals, minimise maladaptative responses, better identify competing interests, reduce stakeholder conflict and exploit opportunities for appropriate ecosystem restoration and sustainable development.

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

    SciTech Connect

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

    2015-05-01

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

  11. A practical receding horizon control framework for path planning and control of autonomous vtol vehicles

    NASA Astrophysics Data System (ADS)

    Liu, C.; Chen, W.-H.

    2013-12-01

    This paper describes an integrated path planning and tracking control framework for autonomous vertical-take-off-and-landing (VTOL) vehicles, particularly quadrotors. The path planning adopts a receding horizon strategy to repeatedly plan a local trajectory that satisfies both the vehicle dynamics and obstacle-free requirement. A tracking controller is then designed to track the planned path. The differential flatness property of the quadrotor is exploited in both path planner and tracking controller designs. The proposed framework is verified by real-time simulations incorporating online optimization.

  12. Adaptive control of robotic manipulators with structural flexibility

    NASA Astrophysics Data System (ADS)

    Wu, Sijun

    The control problem of mechanically flexible systems was an important issue for the past decade due mainly to the growing needs for fast, precise manipulators in industry and space applications. In this thesis, stable, high precision, and high-bandwidth closed-loop tip position control of a one-link flexible robot was investigated. Two adaptive control methods are developed and studied. A non-dimensionalized dynamic model for the flexible robot arm is developed. Payload mass and moment of inertia are also considered in the modeling. It can be shown that with a set of strain gauge measurements, the payload mass and moment of inertia could be estimated. This provides a convenient tool to detect the variations of the payload, which is crucial for precision control. The lattice filter used in the tip position control of a flexible arm proves to be a good parameter identifier in the on-line identification of the robot due to its high convergence rate and noise rejection capability. Although the lattice filter is usualy designed for auto-regressive or moving-average processes, its applications are extended to include auto-regressive and moving-average processes. The proposed model reference adaptive inverse controller is in the form of a series type of model reference system. It differs from other model reference controller in that the forward controller is the identified systems inverse. Moreover, an additional control signal is applied which comes from a signal synthesis block to compensate the output tracking and parameter identification errors. Compared with other control techniques such as stable factorization and linear quadratic Gaussian, the predictive adaptive controller could provide faster control with reasonably low input energy level.

  13. An Adaptive Multilevel Security Framework for the Data Stored in Cloud Environment.

    PubMed

    Dorairaj, Sudha Devi; Kaliannan, Thilagavathy

    2015-01-01

    Cloud computing is renowned for delivering information technology services based on internet. Nowadays, organizations are interested in moving their massive data and computations into cloud to reap their significant benefits of on demand service, resource pooling, and rapid elasticity that helps to satisfy the dynamically changing infrastructure demand without the burden of owning, managing, and maintaining it. Since the data needs to be secured throughout its life cycle, security of the data in cloud is a major challenge to be concentrated on because the data is in third party's premises. Any uniform simple or high level security method for all the data either compromises the sensitive data or proves to be too costly with increased overhead. Any common multiple method for all data becomes vulnerable when the common security pattern is identified at the event of successful attack on any information and also encourages more attacks on all other data. This paper suggests an adaptive multilevel security framework based on cryptography techniques that provide adequate security for the classified data stored in cloud. The proposed security system acclimates well for cloud environment and is also customizable and more reliant to meet the required level of security of data with different sensitivity that changes with business needs and commercial conditions. PMID:26258165

  14. Re-engineering cities: a framework for adaptation to global change.

    PubMed

    Dawson, Richard

    2007-12-15

    Urban areas are expected to continue their rapid growth in the twenty-first century. Globally, cities are major sources of greenhouse gases emissions and their high population densities make them potential focal points of vulnerability to global environmental change. Moreover, their reach, in terms of flows of materials and resources, extends far outside their borders. Evidently, it is no longer tenable to consider urban systems to be static artefacts constructed in a stable environment, nor continue to divorce them from the global context that influences many of the climatic and socio-economic changes within cities. Furthermore, the uncertainty in the future climatic and socio-economic conditions poses significant challenges for planners. A framework is proposed for analysing urban systems with evidence-based tools over extended time scales. This forms the basis of a manifesto for future challenges and research directions for this critical subject area, which ultimately will help engineers and urban planners to better understand the areas for which they are responsible and to develop adaptation strategies that can tackle the challenges posed by long-term global change and lead to more sustainable cities.

  15. An Adaptive Framework for Real-Time ECG Transmission in Mobile Environments

    PubMed Central

    2014-01-01

    Wireless electrocardiogram (ECG) monitoring involves the measurement of ECG signals and their timely transmission over wireless networks to remote healthcare professionals. However, fluctuations in wireless channel conditions pose quality-of-service challenges for real-time ECG monitoring services in a mobile environment. We present an adaptive framework for layered coding and transmission of ECG data that can cope with a time-varying wireless channel. The ECG is segmented into layers with differing importance with respect to the quality of the reconstructed signal. According to this observation, we have devised a simple and efficient real-time scheduling algorithm based on the earliest deadline first (EDF) policy, which decides the order of transmitting or retransmitting packets that contain ECG data at any given time for the delivery of scalable ECG data over a lossy channel. The algorithm takes into account the differing priorities of packets in each layer, which prevents the perceived quality of the reconstructed ECG signal from degrading abruptly as channel conditions worsen, while using the available bandwidth efficiently. Extensive simulations demonstrate this improvement in perceived quality. PMID:25097886

  16. A fully automatic framework for cell segmentation on non-confocal adaptive optics images

    NASA Astrophysics Data System (ADS)

    Liu, Jianfei; Dubra, Alfredo; Tam, Johnny

    2016-03-01

    By the time most retinal diseases are diagnosed, macroscopic irreversible cellular loss has already occurred. Earlier detection of subtle structural changes at the single photoreceptor level is now possible, using the adaptive optics scanning light ophthalmoscope (AOSLO). This work aims to develop a fully automatic segmentation framework to extract cell boundaries from non-confocal split-detection AOSLO images of the cone photoreceptor mosaic in the living human eye. Significant challenges include anisotropy, heterogeneous cell regions arising from shading effects, and low contrast between cells and background. To overcome these challenges, we propose the use of: 1) multi-scale Hessian response to detect heterogeneous cell regions, 2) convex hulls to create boundary templates, and 3) circularlyconstrained geodesic active contours to refine cell boundaries. We acquired images from three healthy subjects at eccentric retinal regions and manually contoured cells to generate ground-truth for evaluating segmentation accuracy. Dice coefficient, relative absolute area difference, and average contour distance were 82±2%, 11±6%, and 2.0±0.2 pixels (Mean±SD), respectively. We find that strong shading effects from vessels are a main factor that causes cell oversegmentation and false segmentation of non-cell regions. Our segmentation algorithm can automatically and accurately segment photoreceptor cells on non-confocal AOSLO images, which is the first step in longitudinal tracking of cellular changes in the individual eye over the time course of disease progression.

  17. An Adaptive Multilevel Security Framework for the Data Stored in Cloud Environment

    PubMed Central

    Dorairaj, Sudha Devi; Kaliannan, Thilagavathy

    2015-01-01

    Cloud computing is renowned for delivering information technology services based on internet. Nowadays, organizations are interested in moving their massive data and computations into cloud to reap their significant benefits of on demand service, resource pooling, and rapid elasticity that helps to satisfy the dynamically changing infrastructure demand without the burden of owning, managing, and maintaining it. Since the data needs to be secured throughout its life cycle, security of the data in cloud is a major challenge to be concentrated on because the data is in third party's premises. Any uniform simple or high level security method for all the data either compromises the sensitive data or proves to be too costly with increased overhead. Any common multiple method for all data becomes vulnerable when the common security pattern is identified at the event of successful attack on any information and also encourages more attacks on all other data. This paper suggests an adaptive multilevel security framework based on cryptography techniques that provide adequate security for the classified data stored in cloud. The proposed security system acclimates well for cloud environment and is also customizable and more reliant to meet the required level of security of data with different sensitivity that changes with business needs and commercial conditions. PMID:26258165

  18. Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems

    NASA Technical Reports Server (NTRS)

    Esogbue, Augustine O.

    1998-01-01

    The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of

  19. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    PubMed Central

    Quagliotti, Fulvia

    2014-01-01

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

  20. Adaptive second-order sliding mode control with uncertainty compensation

    NASA Astrophysics Data System (ADS)

    Bartolini, G.; Levant, A.; Pisano, A.; Usai, E.

    2016-09-01

    This paper endows the second-order sliding mode control (2-SMC) approach with additional capabilities of learning and control adaptation. We present a 2-SMC scheme that estimates and compensates for the uncertainties affecting the system dynamics. It also adjusts the discontinuous control effort online, so that it can be reduced to arbitrarily small values. The proposed scheme is particularly useful when the available information regarding the uncertainties is conservative, and the classical `fixed-gain' SMC would inevitably lead to largely oversized discontinuous control effort. Benefits from the viewpoint of chattering reduction are obtained, as confirmed by computer simulations.

  1. F-8C adaptive control law refinement and software development

    NASA Technical Reports Server (NTRS)

    Hartmann, G. L.; Stein, G.

    1981-01-01

    An explicit adaptive control algorithm based on maximum likelihood estimation of parameters was designed. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm was implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer, surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software.

  2. Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.

    PubMed

    Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan

    2016-02-22

    We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.

  3. A framework for the natural-language-perception-based creative control of unmanned ground vehicles

    NASA Astrophysics Data System (ADS)

    Ghaffari, Masoud; Liao, Xiaoqun; Hall, Ernest L.

    2004-09-01

    Mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. That is why mobile robotics problems are complex with many unanswered questions. To reach a high degree of autonomous operation, a new level of learning is required. On the one hand, promising learning theories such as the adaptive critic and creative control have been proposed, while on other hand the human brain"s processing ability has amazed and inspired researchers in the area of Unmanned Ground Vehicles but has been difficult to emulate in practice. A new direction in the fuzzy theory tries to develop a theory to deal with the perceptions conveyed by the natural language. This paper tries to combine these two fields and present a framework for autonomous robot navigation. The proposed creative controller like the adaptive critic controller has information stored in a dynamic database (DB), plus a dynamic task control center (TCC) that functions as a command center to decompose tasks into sub-tasks with different dynamic models and multi-criteria functions. The TCC module utilizes computational theory of perceptions to deal with the high levels of task planning. The authors are currently trying to implement the model on a real mobile robot and the preliminary results have been described in this paper.

  4. CDP - Adaptive Supervisory Control and Data Acquisition (SCADA) Technology for Infrastructure Protection

    SciTech Connect

    Marco Carvalho; Richard Ford

    2012-05-14

    Supervisory Control and Data Acquisition (SCADA) Systems are a type of Industrial Control System characterized by the centralized (or hierarchical) monitoring and control of geographically dispersed assets. SCADA systems combine acquisition and network components to provide data gathering, transmission, and visualization for centralized monitoring and control. However these integrated capabilities, especially when built over legacy systems and protocols, generally result in vulnerabilities that can be exploited by attackers, with potentially disastrous consequences. Our research project proposal was to investigate new approaches for secure and survivable SCADA systems. In particular, we were interested in the resilience and adaptability of large-scale mission-critical monitoring and control infrastructures. Our research proposal was divided in two main tasks. The first task was centered on the design and investigation of algorithms for survivable SCADA systems and a prototype framework demonstration. The second task was centered on the characterization and demonstration of the proposed approach in illustrative scenarios (simulated or emulated).

  5. Robust observer-based adaptive fuzzy sliding mode controller

    NASA Astrophysics Data System (ADS)

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

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

  6. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Montenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of Field Programmable Gate Arrays (FPGA's) in the hardware implementation of fast digital signal processing functions. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used Proportional-Integral-Derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a Digital Signal Processor (DSP) device or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using DSP devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, Pulse Width Modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. An alternative is required for compact implementation of such functionality to withstand the harsh environment encountered on spacemap. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive-control algorithm

  7. Implementation of Adaptive Digital Controllers on Programmable Logic Devices

    NASA Technical Reports Server (NTRS)

    Gwaltney, David A.; King, Kenneth D.; Smith, Keary J.; Monenegro, Justino (Technical Monitor)

    2002-01-01

    Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing. Such capability also makes an FPGA a suitable platform for the digital implementation of closed loop controllers. Other researchers have implemented a variety of closed-loop digital controllers on FPGA's. Some of these controllers include the widely used proportional-integral-derivative (PID) controller, state space controllers, neural network and fuzzy logic based controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM-based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance requirements in a compact form-factor. Generally, a software implementation on a DSP (Digital Signal Processor) or microcontroller is used to implement digital controllers. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSP) devices. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated (PWM) outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. In general, very few DSP devices are produced that are designed to meet any level of radiation tolerance or hardness. The goal of this effort is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. An alternative is required for compact implementation of such functionality to withstand the harsh environment

  8. Adaptive nonlinear control of missiles using neural networks

    NASA Astrophysics Data System (ADS)

    McFarland, Michael Bryan

    Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear

  9. Adaptive boundary control of a flexible manipulator with input saturation

    NASA Astrophysics Data System (ADS)

    Liu, Zhijie; Liu, Jinkun; He, Wei

    2016-06-01

    In this study, we consider the anti-windup design as one of the approaches for the boundary control problem of a flexible manipulator in the presence of system parametric uncertainties, external disturbances and bounded inputs. The dynamics of the system are represented by partial differential equations (PDEs). Using the singular perturbation approach, the PDE model is divided into two simpler subsystems. With the Lyapunov's direct method, an adaptive boundary control scheme is developed to regulate the angular position and suppress the elastic vibration simultaneously and the adaptive laws are designed to compensate for the system parametric uncertainties and the disturbances. The proposed control scheme allows the application of smooth hyperbolic functions, which satisfy physical conditions and input restrictions, be easily realised. Numerical simulations demonstrate the effectiveness of the proposed scheme.

  10. Fixed gain and adaptive techniques for rotorcraft vibration control

    NASA Technical Reports Server (NTRS)

    Roy, R. H.; Saberi, H. A.; Walker, R. A.

    1985-01-01

    The results of an analysis effort performed to demonstrate the feasibility of employing approximate dynamical models and frequency shaped cost functional control law desgin techniques for helicopter vibration suppression are presented. Both fixed gain and adaptive control designs based on linear second order dynamical models were implemented in a detailed Rotor Systems Research Aircraft (RSRA) simulation to validate these active vibration suppression control laws. Approximate models of fuselage flexibility were included in the RSRA simulation in order to more accurately characterize the structural dynamics. The results for both the fixed gain and adaptive approaches are promising and provide a foundation for pursuing further validation in more extensive simulation studies and in wind tunnel and/or flight tests.

  11. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

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

    NASA Technical Reports Server (NTRS)

    Yuan, Bau-San; Book, Wayne J.

    1988-01-01

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

  13. Adaptive Control of a Transport Aircraft Using Differential Thrust

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan

    2009-01-01

    The paper presents an adaptive control technique for a damaged large transport aircraft subject to unknown atmospheric disturbances such as wind gust or turbulence. It is assumed that the damage results in vertical tail loss with no rudder authority, which is replaced with a differential thrust input. The proposed technique uses the adaptive prediction based control design in conjunction with the time scale separation principle, based on the singular perturbation theory. The application of later is necessitated by the fact that the engine response to a throttle command is substantially slow that the angular rate dynamics of the aircraft. It is shown that this control technique guarantees the stability of the closed-loop system and the tracking of a given reference model. The simulation example shows the benefits of the approach.

  14. A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance

    NASA Astrophysics Data System (ADS)

    Sreekumar, Muthuswamy

    2016-07-01

    Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.

  15. Adaptation with disturbance attenuation in nonlinear control systems

    SciTech Connect

    Basar, T.

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

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

    NASA Astrophysics Data System (ADS)

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

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

  17. Beaconless adaptive-optics technique for HEL beam control

    NASA Astrophysics Data System (ADS)

    Khizhnyak, Anatoliy; Markov, Vladimir

    2016-05-01

    Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.

  18. Adaptive control of Space Station during nominal operations with CMGs. [Control Moment Gyroscopes

    NASA Technical Reports Server (NTRS)

    Bishop, R. H.; Paynter, S. J.; Sunkel, J. W.

    1991-01-01

    An adaptive control approach is investigated for the Space Station. The main components of the adaptive controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is the Space Station baseline control law. The control gain calculation is based on linear quadratic regulator theory with eigenvalue placement in a vertical strip. The parameter identification scheme is a real-time recursive extended Kalman filter which estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to compute accurate estimates of the Space Station inertias during nominal CMG (control moment gyro) operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.

  19. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  20. Evaluating success criteria and project monitoring in river enhancement within an adaptive management framework

    USGS Publications Warehouse

    O'Donnell, T. K.; Galat, D.L.

    2008-01-01

    Objective setting, performance measures, and accountability are important components of an adaptive-management approach to river-enhancement programs. Few lessons learned by river-enhancement practitioners in the United States have been documented and disseminated relative to the number of projects implemented. We conducted scripted telephone surveys with river-enhancement project managers and practitioners within the Upper Mississippi River Basin (UMRB) to determine the extent of setting project success criteria, monitoring, evaluation of monitoring data, and data dissemination. Investigation of these elements enabled a determination of those that inhibited adaptive management. Seventy river enhancement projects were surveyed. Only 34% of projects surveyed incorporated a quantified measure of project success. Managers most often relied on geophysical attributes of rivers when setting project success criteria, followed by biological communities. Ninety-one percent of projects that performed monitoring included biologic variables, but the lack of data collection before and after project completion and lack of field-based reference or control sites will make future assessments of ecologic success difficult. Twenty percent of projects that performed monitoring evaluated ???1 variable but did not disseminate their evaluations outside their organization. Results suggest greater incentives may be required to advance the science of river enhancement. Future river-enhancement programs within the UMRB and elsewhere can increase knowledge gained from individual projects by offering better guidance on setting success criteria before project initiation and evaluation through established monitoring protocols. ?? 2007 Springer Science+Business Media, LLC.

  1. Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

    NASA Astrophysics Data System (ADS)

    Eshak, Peter B.

    Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to

  2. Direct model reference adaptive control of a flexible robotic manipulator

    NASA Technical Reports Server (NTRS)

    Meldrum, D. R.

    1985-01-01

    Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.

  3. Robust adaptive backstepping control for reentry reusable launch vehicles

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Wu, Zhong; Du, Yijiang

    2016-09-01

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

  4. Adaptive suboptimal second-order sliding mode control for microgrids

    NASA Astrophysics Data System (ADS)

    Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

    2016-09-01

    This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

  5. An adaptive fuzzy controller for permanent-magnet AC servo drives

    SciTech Connect

    Le-Huy, H.

    1995-12-31

    This paper presents a theoretical study on a model-reference adaptive fuzzy logic controller for vector-controlled permanent-magnet ac servo drives. In the proposed system, fuzzy logic is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The results are compared with that provided by a non-adaptive fuzzy controller. The implementation of proposed adaptive fuzzy controller is discussed.

  6. Towards feasible and effective predictive wavefront control for adaptive optics

    SciTech Connect

    Poyneer, L A; Veran, J

    2008-06-04

    We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

  7. Integrating adjustable autonomy in an intelligent control framework

    NASA Astrophysics Data System (ADS)

    DeKoven, Elyon A. M.; Wood, Scott D.

    2005-10-01

    Currently, multiple humans are needed to operate a single uninhabited aerial vehicle (UAV). In the near future, combat techniques will involve single operators controlling multiple uninhabited ground and air vehicles. This situation creates both technological hurdles as well as interaction design challenges that must be addressed to support future fighters. In particular, the system will need to negotiate with the operator about proper task delegation, keeping the operator appropriately apprised of autonomous actions. This in turn implies that the system must know what the user is doing, what needs to be done in the present situation, and the comparative strengths for of the human and the system in each task. Towards building such systems, we are working on an Intelligent Control Framework (ICF) that provides a layer of intelligence to support future warfighters in complex task environments. The present paper presents the Adjustable Autonomy Module (AAM) in ICF. The AAM encapsulates some capabilities for user plan recognition, situation reasoning, and authority delegation control. The AAM has the knowledge necessary to support operator-system dialogue about autonomy changes, and it also provides the system with the ability to act on this knowledge. Combined with careful interaction design, planning and plan-execution capabilities, the AAM enables future design and development of effective human-robot teams.

  8. Microgravity isolation system design: A modern control analysis framework

    NASA Technical Reports Server (NTRS)

    Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

    1994-01-01

    Many acceleration-sensitive, microgravity science experiments will require active vibration isolation from the manned orbiters on which they will be mounted. The isolation problem, especially in the case of a tethered payload, is a complex three-dimensional one that is best suited to modern-control design methods. These methods, although more powerful than their classical counterparts, can nonetheless go only so far in meeting the design requirements for practical systems. Once a tentative controller design is available, it must still be evaluated to determine whether or not it is fully acceptable, and to compare it with other possible design candidates. Realistically, such evaluation will be an inherent part of a necessary iterative design process. In this paper, an approach is presented for applying complex mu-analysis methods to a closed-loop vibration isolation system (experiment plus controller). An analysis framework is presented for evaluating nominal stability, nominal performance, robust stability, and robust performance of active microgravity isolation systems, with emphasis on the effective use of mu-analysis methods.

  9. Adaptation strategies for health impacts of climate change in Western Australia: Application of a Health Impact Assessment framework

    SciTech Connect

    Spickett, Jeffery T.; Brown, Helen L.; Katscherian, Dianne

    2011-04-15

    Climate change is one of the greatest challenges facing the globe and there is substantial evidence that this will result in a number of health impacts, regardless of the level of greenhouse gas mitigation. It is therefore apparent that a combined approach of mitigation and adaptation will be required to protect public health. While the importance of mitigation is recognised, this project focused on the role of adaptation strategies in addressing the potential health impacts of climate change. The nature and magnitude of these health impacts will be determined by a number of parameters that are dependent upon the location. Firstly, climate change will vary between regions. Secondly, the characteristics of each region in terms of population and the ability to adapt to changes will greatly influence the extent of the health impacts that are experienced now and into the future. Effective adaptation measures therefore need to be developed with these differences in mind. A Health Impact Assessment (HIA) framework was used to consider the implications of climate change on the health of the population of Western Australia (WA) and to develop a range of adaptive responses suited to WA. A broad range of stakeholders participated in the HIA process, providing informed input into developing an understanding of the potential health impacts and potential adaptation strategies from a diverse sector perspective. Potential health impacts were identified in relation to climate change predictions in WA in the year 2030. The risk associated with each of these impacts was assessed using a qualitative process that considered the consequences and the likelihood of the health impact occurring. Adaptations were then developed which could be used to mitigate the identified health impacts and provide responses which could be used by Government for future decision making. The periodic application of a HIA framework is seen as an ideal tool to develop appropriate adaptation strategies to

  10. A trait-based framework for predicting when and where microbial adaptation to climate change will affect ecosystem functioning

    USGS Publications Warehouse

    Wallenstein, Matthew D.; Hall, Edward K.

    2012-01-01

    As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.

  11. Visuomotor Control of Human Adaptive Locomotion: Understanding the Anticipatory Nature

    PubMed Central

    Higuchi, Takahiro

    2013-01-01

    To maintain balance during locomotion, the central nervous system (CNS) accommodates changes in the constraints of spatial environment (e.g., existence of an obstacle or changes in the surface properties). Locomotion while modifying the basic movement patterns in response to such constraints is referred to as adaptive locomotion. The most powerful means of ensuring balance during adaptive locomotion is to visually perceive the environmental properties at a distance and modify the movement patterns in an anticipatory manner to avoid perturbation altogether. For this reason, visuomotor control of adaptive locomotion is characterized, at least in part, by its anticipatory nature. The purpose of the present article is to review the relevant studies which revealed the anticipatory nature of the visuomotor control of adaptive locomotion. The anticipatory locomotor adjustments for stationary and changeable environment, as well as the spatio-temporal patterns of gaze behavior to support the anticipatory locomotor adjustments are described. Such description will clearly show that anticipatory locomotor adjustments are initiated when an object of interest (e.g., a goal or obstacle) still exists in far space. This review also show that, as a prerequisite of anticipatory locomotor adjustments, environmental properties are accurately perceived from a distance in relation to individual’s action capabilities. PMID:23720647

  12. Effect of prism adaptation on thermoregulatory control in humans.

    PubMed

    Calzolari, Elena; Gallace, Alberto; Moseley, G Lorimer; Vallar, Giuseppe

    2016-01-01

    The physiological regulation of skin temperature can be modulated not only by autonomic brain regions, but also by a network of higher-level cortical areas involved in the maintenance of a coherent representation of the body. In this study we assessed in healthy participants if the sensorimotor changes taking place during motor adaptation to the lateral displacement of the visual scene induced by wearing prismatic lenses (prism adaptation, PA), and the aftereffects, after prisms' removal, on the ability to process spatial coordinates, were associated with skin temperature regulation changes. We found a difference in thermoregulatory control as a function of the direction of the prism-induced displacement of the visual scene, and the subsequent sensorimotor adaptation. After PA to rightward displacing lenses, with leftward aftereffects (the same directional procedure efficaciously used for ameliorating left spatial neglect in right-brain-damaged patients) the hands' temperature decreased. Conversely, after adaptation to neutral lenses, and PA to leftward displacing lenses, with rightward aftereffects, the temperature of both hands increased. These results suggest a lateral asymmetry in the effects of PA on skin temperature regulation, and a relationship between body spatial representations and homeostatic control in humans.

  13. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    NASA Astrophysics Data System (ADS)

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  14. Minimal control synthesis adaptive control of nonlinear systems: utilizing the properties of chaos.

    PubMed

    di Bernardo, M; Stoten, D P

    2006-09-15

    This paper discusses a novel approach to the control of chaos based on the use of the adaptive minimal control synthesis algorithm. The strategies presented are based on the explicit exploitation of different properties of chaotic systems including the boundedness of the chaotic attractors and their topological transitivity (or ergodicity). It is shown that chaos can be exploited to synthesize more efficient control techniques for nonlinear systems. For instance, by using the ergodicity of the chaotic trajectory, we show that a local adaptive control strategy can be used to synthesize a global controller. An application is to the swing-up control of a double inverted pendulum. PMID:16893794

  15. Geometry adaptive control of a composite reflector using PZT actuator

    NASA Astrophysics Data System (ADS)

    Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang

    2015-04-01

    Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.

  16. An adaptive learning control system for large flexible structures

    NASA Technical Reports Server (NTRS)

    Thau, F. E.

    1985-01-01

    The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

  17. Adaptive and predictive control of a simulated robot arm.

    PubMed

    Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

    2013-06-01

    In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs).

  18. Application of network control systems for adaptive optics

    NASA Astrophysics Data System (ADS)

    Eager, Robert J.

    2008-04-01

    The communication architecture for most pointing, tracking, and high order adaptive optics control systems has been based on a centralized point-to-point and bus based approach. With the increased use of larger arrays and multiple sensors, actuators and processing nodes, these evolving systems require decentralized control, modularity, flexibility redundancy, integrated diagnostics, dynamic resource allocation, and ease of maintenance to support a wide range of experiments. Network control systems provide all of these critical functionalities. This paper begins with a quick overview of adaptive optics as a control system and communication architecture. It then provides an introduction to network control systems, identifying the key design areas that impact system performance. The paper then discusses the performance test results of a fielded network control system used to implement an adaptive optics system comprised of: a 10KHz, 32x32 spatial selfreferencing interferometer wave front sensor, a 705 channel "Tweeter" deformable mirror, a 177 channel "Woofer" deformable mirror, ten processing nodes, and six data acquisition nodes. The reconstructor algorithm utilized a modulo-2pi wave front phase measurement and a least-squares phase un-wrapper with branch point correction. The servo control algorithm is a hybrid of exponential and infinite impulse response controllers, with tweeter-to-woofer saturation offloading. This system achieved a first-pixel-out to last-mirror-voltage latency of 86 microseconds, with the network accounting for 4 microseconds of the measured latency. Finally, the extensibility of this architecture will be illustrated, by detailing the integration of a tracking sub-system into the existing network.

  19. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  20. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  1. Fuzzy-based adaptive bandwidth control for loss guarantees.

    PubMed

    Siripongwutikorn, Peerapon; Banerjee, Sujata; Tipper, David

    2005-09-01

    This paper presents the use of adaptive bandwidth control (ABC) for a quantitative packet loss rate guarantee to aggregate traffic in packet switched networks. ABC starts with some initial amount of bandwidth allocated to a queue and adjusts it over time based on online measurements of system states to ensure that the allocated bandwidth is just enough to attain the specified loss requirement. Consequently, no a priori detailed traffic information is required, making ABC more suitable for efficient aggregate quality of service (QoS) provisioning. We propose an ABC algorithm called augmented Fuzzy (A-Fuzzy) control, whereby fuzzy logic control is used to keep an average queue length at an appropriate target value, and the measured packet loss rate is used to augment the standard control to achieve better performance. An extensive simulation study based on both theoretical traffic models and real traffic traces under a wide range of system configurations demonstrates that the A-Fuzzy control itself is highly robust, yields high bandwidth utilization, and is indeed a viable alternative and improvement to static bandwidth allocation (SBA) and existing adaptive bandwidth allocation schemes. Additionally, we develop a simple and efficient measurement-based admission control procedure which limits the amount of input traffic in order to maintain the performance of the A-Fuzzy control at an acceptable level.

  2. Discrete-time minimal control synthesis adaptive algorithm

    NASA Astrophysics Data System (ADS)

    di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.

    2010-12-01

    This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.

  3. An adaptive decision framework for the conservation of a threatened plant

    USGS Publications Warehouse

    Moore, Clinton T.; Fonnesbeck, Christopher J.; Shea, Katriona; Lah, Kristopher J.; McKenzie, Paul M.; Ball, Lianne C.; Runge, Michael C.; Alexander, Helen M.

    2011-01-01

    Mead's milkweed Asclepias meadii, a long-lived perennial herb of tallgrass prairie and glade communities of the central United States, is a species designated as threatened under the U.S. Endangered Species Act. Challenges to its successful management include the facts that much about its life history is unknown, its age at reproductive maturity is very advanced, certain life stages are practically unobservable, its productivity is responsive to unpredictable environmental events, and most of the known populations occur on private lands unprotected by any legal conservation instrument. One critical source of biological uncertainty is the degree to which fire promotes growth and reproductive response in the plant. To aid in its management, we developed a prototype population-level state-dependent decision-making framework that explicitly accounts for this uncertainty and for uncertainties related to stochastic environmental effects and vital rates. To parameterize the decision model, we used estimates found in the literature, and we analyzed data from a long-term monitoring program where fates of individual plants were observed through time. We demonstrate that different optimal courses of action are followed according to how one believes that fire influences reproductive response, and we show that the action taken for certain population states is informative for resolving uncertainty about competing beliefs regarding the effect of fire. We advocate the use of a model-predictive approach for the management of rare populations, particularly when management uncertainty is profound. Over time, an adaptive management approach should reduce uncertainty and improve management performance as predictions of management outcome generated under competing models are continually informed and updated by monitoring data.

  4. Adaptive pitch control for variable speed wind turbines

    DOEpatents

    Johnson, Kathryn E.; Fingersh, Lee Jay

    2012-05-08

    An adaptive method for adjusting blade pitch angle, and controllers implementing such a method, for achieving higher power coefficients. Average power coefficients are determined for first and second periods of operation for the wind turbine. When the average power coefficient for the second time period is larger than for the first, a pitch increment, which may be generated based on the power coefficients, is added (or the sign is retained) to the nominal pitch angle value for the wind turbine. When the average power coefficient for the second time period is less than for the first, the pitch increment is subtracted (or the sign is changed). A control signal is generated based on the adapted pitch angle value and sent to blade pitch actuators that act to change the pitch angle of the wind turbine to the new or modified pitch angle setting, and this process is iteratively performed.

  5. Controller-structure interaction compensation using adaptive residual mode filters

    NASA Technical Reports Server (NTRS)

    Davidson, Roger A.; Balas, Mark J.

    1990-01-01

    It is not feasible to construct controllers for large space structures or large scale systems (LSS's) which are of the same order as the structures. The complexity of the dynamics of these systems is such that full knowledge of its behavior cannot by processed by today's controller design methods. The controller for system performance of such a system is therefore based on a much smaller reduced-order model (ROM). Unfortunately, the interaction between the LSS and the ROM-based controller can produce instabilities in the closed-loop system due to the unmodeled dynamics of the LSS. Residual mode filters (RMF's) allow the systematic removal of these instabilities in a matter which does not require a redesign of the controller. In addition RMF's have a strong theoretical basis. As simple first- or second-order filters, the RMF CSI compensation technique is at once modular, simple and highly effective. RMF compensation requires knowledge of the dynamics of the system modes which resulted in the previous closed-loop instabilities (the residual modes), but this information is sometimes known imperfectly. An adaptive, self-tuning RMF design, which compensates for uncertainty in the frequency of the residual mode, has been simulated using continuous-time and discrete-time models of a flexible robot manipulator. Work has also been completed on the discrete-time experimental implementation on the Martin Marietta flexible robot manipulator experiment. This paper will present the results of that work on adaptive, self-tuning RMF's, and will clearly show the advantage of this adaptive compensation technique for controller-structure interaction (CSI) instabilities in actively-controlled LSS's.

  6. Scenario Planning Provides a Framework for Climate Change Adaptation in the National Park Service

    NASA Astrophysics Data System (ADS)

    Welling, L. A.

    2012-12-01

    Resource management decisions must be based on future expectations. Abundant evidence suggests climate change will have highly consequential effects on the Nation's natural and cultural resources, but specific impacts are difficult to accurately predict. This situation of too much information but not enough specificity can often lead to either paralysis or denial for decision makers. Scenario planning is an emerging tool for climate change adaptation that provides a structured framework for identifying and exploring critical drivers of change and their uncertain outcomes. Since 2007, the National Park Service (NPS) has been working with its partners to develop and apply a scenario-based approach for adaptation planning that integrates quantitative, model-driven, climate change projections with qualitative, participatory exercises to explore management and policy options under a range of future conditions. Major outcomes of this work are (1) increased understanding of key scientific results and uncertainties, (2) incorporation of alternative perspectives into park and landscape level planning, (3) identification of "no brainer" and "no gainer" actions, (4) strengthening of regional science-management partnerships, and (5) overall improved capacity for flexible decision making. The basic approach employed by NPS for scenario planning follows a typical adaptive management process: define the focal question, assess the relevant science, explore plausible futures, identify effective strategies, prioritize and implement actions, and monitor results. Many science and management partners contributed to the process, including NOAA Regional Integrated Science and Assessment teams (RISAs) and Regional Climate Centers (RCCs), USGS Research Centers, and other university and government scientists. The Global Business Network, an internationally recognized leader in scenario development, provided expert facilitation and training techniques. Climate science input is provided

  7. Refinement and evaluation of helicopter real-time self-adaptive active vibration controller algorithms

    NASA Technical Reports Server (NTRS)

    Davis, M. W.

    1984-01-01

    A Real-Time Self-Adaptive (RTSA) active vibration controller was used as the framework in developing a computer program for a generic controller that can be used to alleviate helicopter vibration. Based upon on-line identification of system parameters, the generic controller minimizes vibration in the fuselage by closed-loop implementation of higher harmonic control in the main rotor system. The new generic controller incorporates a set of improved algorithms that gives the capability to readily define many different configurations by selecting one of three different controller types (deterministic, cautious, and dual), one of two linear system models (local and global), and one or more of several methods of applying limits on control inputs (external and/or internal limits on higher harmonic pitch amplitude and rate). A helicopter rotor simulation analysis was used to evaluate the algorithms associated with the alternative controller types as applied to the four-bladed H-34 rotor mounted on the NASA Ames Rotor Test Apparatus (RTA) which represents the fuselage. After proper tuning all three controllers provide more effective vibration reduction and converge more quickly and smoothly with smaller control inputs than the initial RTSA controller (deterministic with external pitch-rate limiting). It is demonstrated that internal limiting of the control inputs a significantly improves the overall performance of the deterministic controller.

  8. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    NASA Astrophysics Data System (ADS)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    that met the DM's preference criteria, therefore allowing the expert to select among several strong candidate designs depending on her/his LTM budget, c) two of the methodologies - Case-Based Micro Interactive Genetic Algorithm (CBMIGA) and Interactive Genetic Algorithm with Mixed Initiative Interaction (IGAMII) - were also able to assist in controlling human fatigue and adapt to the DM's learning process.

  9. THE EFFECTS OF BRAIN LATERALIZATION ON MOTOR CONTROL AND ADAPTATION

    PubMed Central

    Mutha, Pratik K.; Haaland, Kathleen Y.; Sainburg, Robert L.

    2012-01-01

    Lateralization of mechanisms mediating functions such as language and perception is widely accepted as a fundamental feature of neural organization. Recent research has revealed that a similar organization exists for the control of motor actions, in that each brain hemisphere contributes unique control mechanisms to the movements of each arm. We now review current research that addresses the nature of the control mechanisms that are lateralized to each hemisphere and how they impact motor adaptation and learning. In general, the studies reviewed here suggest an enhanced role for the left hemisphere during adaptation, and the learning of new sequences and skills. We suggest that this specialization emerges from a left hemisphere specialization for predictive control – the ability to effectively plan and coordinate motor actions, possibly by optimizing certain cost functions. In contrast, right hemisphere circuits appear to be important for updating ongoing actions and stopping at a goal position, through modulation of sensorimotor stabilization mechanisms such as reflexes. We also propose that each brain hemisphere contributes its mechanism to the control of both arms. We conclude by examining the potential advantages of such a lateralized control system. PMID:23237468

  10. Adaptive Proactive Inhibitory Control for Embedded Real-Time Applications

    PubMed Central

    Yang, Shufan; McGinnity, T. Martin; Wong-Lin, KongFatt

    2012-01-01

    Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real-time while achieving behavioral performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control. PMID:22701420

  11. Neural controller for adaptive movements with unforeseen payloads

    NASA Technical Reports Server (NTRS)

    Kuperstein, Michael; Wang, Jyhpyng

    1990-01-01

    A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated information about payload and actuator limits. Its average positioning accuracy across a large range of payloads after learning is 3 percent of the positioning range. This neural controller can be used as a basis for coordinating any number of sensory inputs with limbs of any number of joints. The feedforward nature of control allows parallel implementation in real time across multiple joints.

  12. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices

    NASA Astrophysics Data System (ADS)

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-10-01

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

  13. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

    PubMed

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-10-21

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

  14. Mechanisms in Adaptive Feedback Control: Photoisomerization in a Liquid

    SciTech Connect

    Hoki, Kunihito; Brumer, Paul

    2005-10-14

    The underlying mechanism for Adaptive Feedback Control in the experimental photoisomerization of 3,3'-diethyl-2,2'-thiacyanine iodide (NK88) in methanol is exposed theoretically. With given laboratory limitations on laser output, the complicated electric fields are shown to achieve their targets in qualitatively simple ways. Further, control over the cis population without laser limitations reveals an incoherent pump-dump scenario as the optimal isomerization strategy. In neither case are there substantial contributions from quantum multiple-path interference or from nuclear wave packet coherence. Environmentally induced decoherence is shown to justify the use of a simplified theoretical model.

  15. An experimental study of a hybrid adaptive control system

    NASA Technical Reports Server (NTRS)

    Lizewski, E. F.; Monopoli, R. V.

    1974-01-01

    A Liapunov type model reference adaptive control system with five adjustable gains is implemented using a PDP-11 digital computer and an EAI 380 analog computer. The plant controlled is a laboratory type dc servo system. It is made to follow closely a second order linear model. The experimental results demonstrate the feasibility of implementing this rather complex design using only a minicomputer and a reasonable number of operational amplifiers. Also, it points out that satisfactory performance can be achieved even when certain assumptions necessary for the theory are not satisfied.

  16. Prediction and control of chaotic processes using nonlinear adaptive networks

    SciTech Connect

    Jones, R.D.; Barnes, C.W.; Flake, G.W.; Lee, K.; Lewis, P.S.; O'Rouke, M.K.; Qian, S.

    1990-01-01

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

  17. An Adaptive Buddy Check for Observational Quality Control

    NASA Technical Reports Server (NTRS)

    Dee, Dick P.; Rukhovets, Leonid; Todling, Ricardo; DaSilva, Arlindo M.; Larson, Jay W.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.

  18. Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.

    PubMed

    Liu, Jie

    2015-04-01

    The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications.

  19. A Framework for Flood Risk Analysis and Benefit Assessment of Flood Control Measures in Urban Areas

    PubMed Central

    Li, Chaochao; Cheng, Xiaotao; Li, Na; Du, Xiaohe; Yu, Qian; Kan, Guangyuan

    2016-01-01

    Flood risk analysis is more complex in urban areas than that in rural areas because of their closely packed buildings, different kinds of land uses, and large number of flood control works and drainage systems. The purpose of this paper is to propose a practical framework for flood risk analysis and benefit assessment of flood control measures in urban areas. Based on the concept of disaster risk triangle (hazard, vulnerability and exposure), a comprehensive analysis method and a general procedure were proposed for urban flood risk analysis. Urban Flood Simulation Model (UFSM) and Urban Flood Damage Assessment Model (UFDAM) were integrated to estimate the flood risk in the Pudong flood protection area (Shanghai, China). S-shaped functions were adopted to represent flood return period and damage (R-D) curves. The study results show that flood control works could significantly reduce the flood risk within the 66-year flood return period and the flood risk was reduced by 15.59%. However, the flood risk was only reduced by 7.06% when the flood return period exceeded 66-years. Hence, it is difficult to meet the increasing demands for flood control solely relying on structural measures. The R-D function is suitable to describe the changes of flood control capacity. This frame work can assess the flood risk reduction due to flood control measures, and provide crucial information for strategy development and planning adaptation. PMID:27527202

  20. A Framework for Flood Risk Analysis and Benefit Assessment of Flood Control Measures in Urban Areas.

    PubMed

    Li, Chaochao; Cheng, Xiaotao; Li, Na; Du, Xiaohe; Yu, Qian; Kan, Guangyuan

    2016-01-01

    Flood risk analysis is more complex in urban areas than that in rural areas because of their closely packed buildings, different kinds of land uses, and large number of flood control works and drainage systems. The purpose of this paper is to propose a practical framework for flood risk analysis and benefit assessment of flood control measures in urban areas. Based on the concept of disaster risk triangle (hazard, vulnerability and exposure), a comprehensive analysis method and a general procedure were proposed for urban flood risk analysis. Urban Flood Simulation Model (UFSM) and Urban Flood Damage Assessment Model (UFDAM) were integrated to estimate the flood risk in the Pudong flood protection area (Shanghai, China). S-shaped functions were adopted to represent flood return period and damage (R-D) curves. The study results show that flood control works could significantly reduce the flood risk within the 66-year flood return period and the flood risk was reduced by 15.59%. However, the flood risk was only reduced by 7.06% when the flood return period exceeded 66-years. Hence, it is difficult to meet the increasing demands for flood control solely relying on structural measures. The R-D function is suitable to describe the changes of flood control capacity. This frame work can assess the flood risk reduction due to flood control measures, and provide crucial information for strategy development and planning adaptation. PMID:27527202

  1. A Framework for Flood Risk Analysis and Benefit Assessment of Flood Control Measures in Urban Areas.

    PubMed

    Li, Chaochao; Cheng, Xiaotao; Li, Na; Du, Xiaohe; Yu, Qian; Kan, Guangyuan

    2016-08-05

    Flood risk analysis is more complex in urban areas than that in rural areas because of their closely packed buildings, different kinds of land uses, and large number of flood control works and drainage systems. The purpose of this paper is to propose a practical framework for flood risk analysis and benefit assessment of flood control measures in urban areas. Based on the concept of disaster risk triangle (hazard, vulnerability and exposure), a comprehensive analysis method and a general procedure were proposed for urban flood risk analysis. Urban Flood Simulation Model (UFSM) and Urban Flood Damage Assessment Model (UFDAM) were integrated to estimate the flood risk in the Pudong flood protection area (Shanghai, China). S-shaped functions were adopted to represent flood return period and damage (R-D) curves. The study results show that flood control works could significantly reduce the flood risk within the 66-year flood return period and the flood risk was reduced by 15.59%. However, the flood risk was only reduced by 7.06% when the flood return period exceeded 66-years. Hence, it is difficult to meet the increasing demands for flood control solely relying on structural measures. The R-D function is suitable to describe the changes of flood control capacity. This frame work can assess the flood risk reduction due to flood control measures, and provide crucial information for strategy development and planning adaptation.

  2. Adaptive dynamic programming as a theory of sensorimotor control.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-08-01

    Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment.

  3. Adaptive dynamic programming as a theory of sensorimotor control.

    PubMed

    Jiang, Yu; Jiang, Zhong-Ping

    2014-08-01

    Many characteristics of sensorimotor control can be explained by models based on optimization and optimal control theories. However, most of the previous models assume that the central nervous system has access to the precise knowledge of the sensorimotor system and its interacting environment. This viewpoint is difficult to be justified theoretically and has not been convincingly validated by experiments. To address this problem, this paper presents a new computational mechanism for sensorimotor control from a perspective of adaptive dynamic programming (ADP), which shares some features of reinforcement learning. The ADP-based model for sensorimotor control suggests that a command signal for the human movement is derived directly from the real-time sensory data, without the need to identify the system dynamics. An iterative learning scheme based on the proposed ADP theory is developed, along with rigorous convergence analysis. Interestingly, the computational model as advocated here is able to reproduce the motor learning behavior observed in experiments where a divergent force field or velocity-dependent force field was present. In addition, this modeling strategy provides a clear way to perform stability analysis of the overall system. Hence, we conjecture that human sensorimotor systems use an ADP-type mechanism to control movements and to achieve successful adaptation to uncertainties present in the environment. PMID:24962078

  4. A multi-granular-based fuzzy adaptive controller

    NASA Astrophysics Data System (ADS)

    Lu, Bin

    2006-11-01

    The accuracy and complexity of fuzzy control systems are problems worthy of study deeply. The high accuracy of control means that the controlled variables will have to be represented at fine granularity which increases the complexity of controller. To attain the prescribed accuracy in reducing control complexity, a multi-granular fuzzy adaptive controller is proposed which represents the process of reaching goal at different spaces of the information granularity. When the prescribed accuracy is low, a coarse fuzzy controller can be used. As the process moves from high level to low level, the prescribed accuracy becomes higher and the information granularity to fuzzy controller becomes finer. In this controller, a rough plan is generated to reach the final goal firstly. Then, the plan is decomposed to many sub-goals which are submitted to the next lower level of hierarchy. And the more refined plans to reach these sub-goals are determined. If needed, this process of successive refinement continues until the final prescribed accuracy is obtained. In addition, the methods are presented to determine the depth of levels and the number of granules in each level. Finally, the simulation results of double inverted pendulum indicate the effectiveness of the proposed controller.

  5. 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.

  6. Speed tracking and synchronization of multiple motors using ring coupling control and adaptive sliding mode control.

    PubMed

    Li, Le-Bao; Sun, Ling-Ling; Zhang, Sheng-Zhou; Yang, Qing-Quan

    2015-09-01

    A new control approach for speed tracking and synchronization of multiple motors is developed, by incorporating an adaptive sliding mode control (ASMC) technique into a ring coupling synchronization control structure. This control approach can stabilize speed tracking of each motor and synchronize its motion with other motors' motion so that speed tracking errors and synchronization errors converge to zero. Moreover, an adaptive law is exploited to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort and attenuate chattering. Performance comparisons with parallel control, relative coupling control and conventional PI control are investigated on a four-motor synchronization control system. Extensive simulation results show the effectiveness of the proposed control scheme.

  7. Direct model reference adaptive control of robotic arms

    NASA Technical Reports Server (NTRS)

    Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

    1993-01-01

    The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

  8. Adaptive control of a vibratory angle measuring gyroscope.

    PubMed

    Park, Sungsu

    2010-01-01

    This paper presents an adaptive control algorithm for realizing a vibratory angle measuring gyroscope so that rotation angle can be directly measured without integration of angular rate, thus eliminating the accumulation of numerical integration errors. The proposed control algorithm uses a trajectory following approach and the reference trajectory is generated by an ideal angle measuring gyroscope driven by the estimate of angular rate and the auxiliary sinusoidal input so that the persistent excitation condition is satisfied. The developed control algorithm can compensate for all types of fabrication imperfections such as coupled damping and stiffness, and mismatched stiffness and un-equal damping term in an on-line fashion. The simulation results show the feasibility and effectiveness of the developed control algorithm that is capable of directly measuring rotation angle without the integration of angular rate.

  9. Direct model reference adaptive control of robotic arms

    NASA Astrophysics Data System (ADS)

    Kaufman, Howard; Swift, David C.; Cummings, Steven T.; Shankey, Jeffrey R.

    1993-12-01

    The results of controlling A PUMA 560 Robotic Manipulator and the NASA shuttle Remote Manipulator System (RMS) using a Command Generator Tracker (CGT) based Model Reference Adaptive Controller (DMRAC) are presented. Initially, the DMRAC algorithm was run in simulation using a detailed dynamic model of the PUMA 560. The algorithm was tuned on the simulation and then used to control the manipulator using minimum jerk trajectories as the desired reference inputs. The ability to track a trajectory in the presence of load changes was also investigated in the simulation. Satisfactory performance was achieved in both simulation and on the actual robot. The obtained responses showed that the algorithm was robust in the presence of sudden load changes. Because these results indicate that the DMRAC algorithm can indeed be successfully applied to the control of robotic manipulators, additional testing was performed to validate the applicability of DMRAC to simulated dynamics of the shuttle RMS.

  10. A framework for developing an evidence-based, comprehensive tobacco control program

    PubMed Central

    2010-01-01

    Background Tobacco control is an area where the translation of evidence into policy would seem to be straightforward, given the wealth of epidemiological, behavioural and other types of research available. Yet, even here challenges exist. These include information overload, concealment of key (industry-funded) evidence, contextualization, assessment of population impact, and the changing nature of the threat. Methods In the context of Israel's health targeting initiative, Healthy Israel 2020, we describe the steps taken to develop a comprehensive tobacco control strategy. We elaborate on the following: a) scientific issues influencing the choice of tobacco control strategies; b) organization of existing evidence of effectiveness of interventions into a manageable form, and c) consideration of relevant philosophical and political issues. We propose a framework for developing a plan and illustrate this process with a case study in Israel. Results Broad consensus exists regarding the effectiveness of most interventions, but current recommendations differ in the emphasis they place on different strategies. Scientific challenges include integration of complex and sometimes conflicting information from authoritative sources, and lack of estimates of population impact of interventions. Philosophical and political challenges include the use of evidence-based versus innovative policymaking, the importance of individual versus governmental responsibility, and whether and how interventions should be prioritized. The proposed framework includes: 1) compilation of a list of potential interventions 2) modification of that list based on local needs and political constraints; 3) streamlining the list by categorizing interventions into broad groupings of related interventions; together these groupings form the basis of a comprehensive plan; and 4) refinement of the plan by comparing it to existing comprehensive plans. Conclusions Development of a comprehensive tobacco control plan

  11. Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.

    PubMed

    Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing

    2011-12-01

    For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.

  12. Missouri River Emergent Sandbar Habitat Monitoring Plan - A Conceptual Framework for Adaptive Management

    USGS Publications Warehouse

    Sherfy, Mark H.; Stucker, Jennifer H.; Anteau, Michael J.

    2009-01-01

    available to quantify changes in managed habitats for least terns and piping plovers, so that management effectiveness can be evaluated. Extremely high flows and flooding of the Missouri River in 1997 created and improved vast amounts of nesting habitat for least terns and piping plovers. Since 1998, there has been an apparent loss and/or degradation of habitat throughout the river system. However, during the same timeframe reservoir water levels have declined, exposing extensive piping plover breeding habitat. For example, 64 percent of adult piping plovers using the Missouri River in 2005 were observed on reservoir habitats, and 43 percent were observed on Lake Sakakawea (Threatened and Endangered Species Section, Omaha District, U.S. Army Corps of Engineers, unpub. data, 2006). Given the vast dynamics of this river and reservoir system, systemwide monitoring of habitat is clearly needed for the U.S. Army Corps of Engineers (USACE) to employ adaptive management (with respect to river operations) to provide most optimal conditions for the maintenance of breeding habitat of least terns and piping plovers. As a result of this need, the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, began work on a habitat monitoring plan in 2005 as a conceptual framework for adaptive management.

  13. An adaptive spoiler to control the transonic shock

    NASA Astrophysics Data System (ADS)

    Bein, Th; Hanselka, H.; Breitbach, E.

    2000-04-01

    Market research predicts, for the aircraft industry, a large growth in the number of passengers as well as the airfreight rate with the result of this leading to increased competition for the European aircraft industry, the efficiency of new aircraft has to be improved drastically. One approach, among others, is the aerodynamic optimization of the wing. The fixed wing is designed optimally only for one flight condition. This flight condition is described by the parameters altitude, mach number and aircraft weight, all of which permanently vary during the mission of the aircraft. Therefore, the aircraft is just periodically near to the chosen design point. To compensate for this major disadvantage, an `adaptive wing' for optimal adaptation and variation of the profile geometry to the actual flight conditions will be developed. Daimler-Benz Aerospace Airbus, Daimler-Benz Research and the German Aerospace Center (DLR) are working as project partners on concepts for a variable camber and a local spoiler bump. In this paper a structural concept developed by the DLR for the adaptive spoiler will be presented. The concept is designed under the aspect of adaptive structural systems and requires a high integration of actuators, sensor and controllers in the structure. Special aspects of the design will be discussed and the first results, analytical, numerical as well as experimental, will be presented. Part of the concept design is also the development of new actuators optimized for the specific problem. A new actuator concept for the adaptive spoiler based on a cylindrical tube and activated either by pressure or multifunctional materials (e.g. shape memory alloys) will additionally be shown.

  14. The reduced order model problem in distributed parameter systems adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Johnson, C. R., Jr.

    1980-01-01

    The research concerning the reduced order model problem in distributed parameter systems is reported. The adaptive control strategy was chosen for investigation in the annular momentum control device. It is noted, that if there is no observation spill over, and no model errors, an indirect adaptive control strategy can be globally stable. Recent publications concerning adaptive control are included.

  15. Adaptive neural-network-based control of robotic manipulators

    NASA Astrophysics Data System (ADS)

    Mitchell, Kyle; Dagli, Cihan H.

    2001-03-01

    Robotic manipulators are beginning to be seen doing more tasks in our environment. Classical controls engineers have long known how to control these automated hands. They have failed to address the continued control of these devices after parts of the control infrastructure have failed. A failed motor or actuator in a manipulator decreases its range of motion and changes its control structure. Most failures however do not render the manipulator useless. This paper will discuss the use of a neural network to actively update the controller design as portions of a manipulator fail. Actuators can become stuck and later free themselves. Motors can lose range of motion or stop completely. Connecting arms can become bent or entangled. Results will be presented on the ability to maintain functionality through a variety of failure modes. The neural network is constructed and tested in a Matlab environment. This allows testing of several neural network techniques such as back propagation and temporal processing without the need to continually reconfigure target hardware. In this paper we will demonstrate that a modified ensemble of back propagation experts can be trained to control a robotic manipulator without the need to calculate the inverse kinematics equations. Further individual experts can be retrained online to allow for adaptive control through changing dynamics. This allows for manipulators to remain in service through failures in the manipulator infrastructure without the need for human intervention into control equations.

  16. Evolving Systems: Adaptive Key Component Control and Inheritance of Passivity and Dissipativity

    NASA Technical Reports Server (NTRS)

    Frost, S. A.; Balas, M. J.

    2010-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. Autonomous assembly of large, complex flexible structures in space is a target application for Evolving Systems. A critical requirement for autonomous assembling structures is that they remain stable during and after assembly. The fundamental topic of inheritance of stability, dissipativity, and passivity in Evolving Systems is the primary focus of this research. In this paper, we develop an adaptive key component controller to restore stability in Nonlinear Evolving Systems that would otherwise fail to inherit the stability traits of their components. We provide sufficient conditions for the use of this novel control method and demonstrate its use on an illustrative example.

  17. Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

  18. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  20. Controls on Extreme Droughts and Adaptation Strategies in Semiarid Regions

    NASA Astrophysics Data System (ADS)

    Scanlon, B. R.; Cook, C.; Fernando, D. N.; LeBlanc, M.

    2012-12-01

    Increasing vulnerability to droughts with reduced per capita water storage, particularly in semiarid regions, underscores the need for predictive understanding of drought controls and development of adaptation strategies for water resources management. In this study we evaluate causes of major droughts in southwest and southcentral US (California and Texas) and southeast Australia (Murray Darling Basin). Impacts of climate cycles (ENSO, PDO, AMO, NAO, IOD) and atmospheric circulation on drought initiation and persistence are examined. Effects of drought on surface water reservoir storage, groundwater storage, irrigation, and crop production are compared. Adaptation strategies being evaluated include water transfers among sectors, particularly from irrigated agriculture to other groups, increasing storage using managed aquifer recharge, water reuse, and development of new water sources (e.g. seawater desalination). It is critical to develop a broad portfolio of water sources to increase resilience to future droughts.