Adaptive designs in clinical trials: why use them, and how to run and report them.

PubMed

Pallmann, Philip; Bedding, Alun W; Choodari-Oskooei, Babak; Dimairo, Munyaradzi; Flight, Laura; Hampson, Lisa V; Holmes, Jane; Mander, Adrian P; Odondi, Lang'o; Sydes, Matthew R; Villar, Sofía S; Wason, James M S; Weir, Christopher J; Wheeler, Graham M; Yap, Christina; Jaki, Thomas

2018-02-28

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial's course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented.We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

An adaptive two-stage dose-response design method for establishing proof of concept.

PubMed

Franchetti, Yoko; Anderson, Stewart J; Sampson, Allan R

2013-01-01

We propose an adaptive two-stage dose-response design where a prespecified adaptation rule is used to add and/or drop treatment arms between the stages. We extend the multiple comparison procedures-modeling (MCP-Mod) approach into a two-stage design. In each stage, we use the same set of candidate dose-response models and test for a dose-response relationship or proof of concept (PoC) via model-associated statistics. The stage-wise test results are then combined to establish "global" PoC using a conditional error function. Our simulation studies showed good and more robust power in our design method compared to conventional and fixed designs.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1972-01-01

A survey was made of the literature devoted to the synthesis of model-tracking adaptive systems based on application of Liapunov's second method. The basic synthesis procedure is introduced and a critical review of extensions made to the theory since 1966 is made. The extensions relate to design for relative stability, reduction of order techniques, design with disturbance, design with time variable parameters, multivariable systems, identification, and an adaptive observer.

Adaptive clinical trial design.

PubMed

Chow, Shein-Chung

2014-01-01

In recent years, the use of adaptive design methods in clinical trials based on accumulated data at interim has received much attention because of its flexibility and efficiency in pharmaceutical/clinical development. In practice, adaptive design may provide the investigators a second chance to modify or redesign the trial while the study is still ongoing. However, it is a concern that a shift in target patient population may occur after significant adaptations are made. In addition, the overall type I error rate may not be preserved. Moreover, the results may not be reliable and hence are difficult to interpret. As indicated by the US Food and Drug Administration draft guidance on adaptive design clinical trials, the adaptive design has to be a prospectively planned opportunity and should be based on information collected within the study, with or without formal statistical hypothesis testing. This article reviews the relative advantages, limitations, and feasibility of commonly considered adaptive designs in clinical trials. Statistical concerns when implementing adaptive designs are also discussed.

Scale Development and Initial Tests of the Multidimensional Complex Adaptive Leadership Scale for School Principals: An Exploratory Mixed Method Study

ERIC Educational Resources Information Center

Özen, Hamit; Turan, Selahattin

2017-01-01

This study was designed to develop the scale of the Complex Adaptive Leadership for School Principals (CAL-SP) and examine its psychometric properties. This was an exploratory mixed method research design (ES-MMD). Both qualitative and quantitative methods were used to develop and assess psychometric properties of the questionnaire. This study…

A modified adjoint-based grid adaptation and error correction method for unstructured grid

NASA Astrophysics Data System (ADS)

Cui, Pengcheng; Li, Bin; Tang, Jing; Chen, Jiangtao; Deng, Youqi

2018-05-01

Grid adaptation is an important strategy to improve the accuracy of output functions (e.g. drag, lift, etc.) in computational fluid dynamics (CFD) analysis and design applications. This paper presents a modified robust grid adaptation and error correction method for reducing simulation errors in integral outputs. The procedure is based on discrete adjoint optimization theory in which the estimated global error of output functions can be directly related to the local residual error. According to this relationship, local residual error contribution can be used as an indicator in a grid adaptation strategy designed to generate refined grids for accurately estimating the output functions. This grid adaptation and error correction method is applied to subsonic and supersonic simulations around three-dimensional configurations. Numerical results demonstrate that the sensitive grids to output functions are detected and refined after grid adaptation, and the accuracy of output functions is obviously improved after error correction. The proposed grid adaptation and error correction method is shown to compare very favorably in terms of output accuracy and computational efficiency relative to the traditional featured-based grid adaptation.

Fuzzy Adaptive Control Design and Discretization for a Class of Nonlinear Uncertain Systems.

PubMed

Zhao, Xudong; Shi, Peng; Zheng, Xiaolong

2016-06-01

In this paper, tracking control problems are investigated for a class of uncertain nonlinear systems in lower triangular form. First, a state-feedback controller is designed by using adaptive backstepping technique and the universal approximation ability of fuzzy logic systems. During the design procedure, a developed method with less computation is proposed by constructing one maximum adaptive parameter. Furthermore, adaptive controllers with nonsymmetric dead-zone are also designed for the systems. Then, a sampled-data control scheme is presented to discretize the obtained continuous-time controller by using the forward Euler method. It is shown that both proposed continuous and discrete controllers can ensure that the system output tracks the target signal with a small bounded error and the other closed-loop signals remain bounded. Two simulation examples are presented to verify the effectiveness and applicability of the proposed new design techniques.

Simple adaptive control system design for a quadrotor with an internal PFC

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

Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto

2014-12-10

The paper deals with an adaptive control system design problem for a four rotor helicopter or quadrotor. A simple adaptive control design scheme with a parallel feedforward compensator (PFC) in the internal loop of the considered quadrotor will be proposed based on the backstepping strategy. As is well known, the backstepping control strategy is one of the advanced control strategy for nonlinear systems. However, the control algorithm will become complex if the system has higher order relative degrees. We will show that one can skip some design steps of the backstepping method by introducing a PFC in the inner loopmore » of the considered quadrotor, so that the structure of the obtained controller will be simplified and a high gain based adaptive feedback control system will be designed. The effectiveness of the proposed method will be confirmed through numerical simulations.« less

Transient analysis of an adaptive system for optimization of design parameters

NASA Technical Reports Server (NTRS)

Bayard, D. S.

1992-01-01

Averaging methods are applied to analyzing and optimizing the transient response associated with the direct adaptive control of an oscillatory second-order minimum-phase system. The analytical design methods developed for a second-order plant can be applied with some approximation to a MIMO flexible structure having a single dominant mode.

An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size.

PubMed

Levin, Gregory P; Emerson, Sarah C; Emerson, Scott S

2014-09-01

Many papers have introduced adaptive clinical trial methods that allow modifications to the sample size based on interim estimates of treatment effect. There has been extensive commentary on type I error control and efficiency considerations, but little research on estimation after an adaptive hypothesis test. We evaluate the reliability and precision of different inferential procedures in the presence of an adaptive design with pre-specified rules for modifying the sampling plan. We extend group sequential orderings of the outcome space based on the stage at stopping, likelihood ratio statistic, and sample mean to the adaptive setting in order to compute median-unbiased point estimates, exact confidence intervals, and P-values uniformly distributed under the null hypothesis. The likelihood ratio ordering is found to average shorter confidence intervals and produce higher probabilities of P-values below important thresholds than alternative approaches. The bias adjusted mean demonstrates the lowest mean squared error among candidate point estimates. A conditional error-based approach in the literature has the benefit of being the only method that accommodates unplanned adaptations. We compare the performance of this and other methods in order to quantify the cost of failing to plan ahead in settings where adaptations could realistically be pre-specified at the design stage. We find the cost to be meaningful for all designs and treatment effects considered, and to be substantial for designs frequently proposed in the literature. © 2014, The International Biometric Society.

Adaptive sampling in research on risk-related behaviors.

PubMed

Thompson, Steven K; Collins, Linda M

2002-11-01

This article introduces adaptive sampling designs to substance use researchers. Adaptive sampling is particularly useful when the population of interest is rare, unevenly distributed, hidden, or hard to reach. Examples of such populations are injection drug users, individuals at high risk for HIV/AIDS, and young adolescents who are nicotine dependent. In conventional sampling, the sampling design is based entirely on a priori information, and is fixed before the study begins. By contrast, in adaptive sampling, the sampling design adapts based on observations made during the survey; for example, drug users may be asked to refer other drug users to the researcher. In the present article several adaptive sampling designs are discussed. Link-tracing designs such as snowball sampling, random walk methods, and network sampling are described, along with adaptive allocation and adaptive cluster sampling. It is stressed that special estimation procedures taking the sampling design into account are needed when adaptive sampling has been used. These procedures yield estimates that are considerably better than conventional estimates. For rare and clustered populations adaptive designs can give substantial gains in efficiency over conventional designs, and for hidden populations link-tracing and other adaptive procedures may provide the only practical way to obtain a sample large enough for the study objectives.

The Importance of Considering Differences in Study Design in Network Meta-analysis: An Application Using Anti-Tumor Necrosis Factor Drugs for Ulcerative Colitis.

PubMed

Cameron, Chris; Ewara, Emmanuel; Wilson, Florence R; Varu, Abhishek; Dyrda, Peter; Hutton, Brian; Ingham, Michael

2017-11-01

Adaptive trial designs present a methodological challenge when performing network meta-analysis (NMA), as data from such adaptive trial designs differ from conventional parallel design randomized controlled trials (RCTs). We aim to illustrate the importance of considering study design when conducting an NMA. Three NMAs comparing anti-tumor necrosis factor drugs for ulcerative colitis were compared and the analyses replicated using Bayesian NMA. The NMA comprised 3 RCTs comparing 4 treatments (adalimumab 40 mg, golimumab 50 mg, golimumab 100 mg, infliximab 5 mg/kg) and placebo. We investigated the impact of incorporating differences in the study design among the 3 RCTs and presented 3 alternative methods on how to convert outcome data derived from one form of adaptive design to more conventional parallel RCTs. Combining RCT results without considering variations in study design resulted in effect estimates that were biased against golimumab. In contrast, using the 3 alternative methods to convert outcome data from one form of adaptive design to a format more consistent with conventional parallel RCTs facilitated more transparent consideration of differences in study design. This approach is more likely to yield appropriate estimates of comparative efficacy when conducting an NMA, which includes treatments that use an alternative study design. RCTs based on adaptive study designs should not be combined with traditional parallel RCT designs in NMA. We have presented potential approaches to convert data from one form of adaptive design to more conventional parallel RCTs to facilitate transparent and less-biased comparisons.

Towards Individualized Online Learning: The Design and Development of an Adaptive Web Based Learning Environment

ERIC Educational Resources Information Center

Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan

2011-01-01

The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…

Design of Unstructured Adaptive (UA) NAS Parallel Benchmark Featuring Irregular, Dynamic Memory Accesses

NASA Technical Reports Server (NTRS)

Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.

Fast spacecraft adaptive attitude tracking control through immersion and invariance design

NASA Astrophysics Data System (ADS)

Wen, Haowei; Yue, Xiaokui; Li, Peng; Yuan, Jianping

2017-10-01

This paper presents a novel non-certainty-equivalence adaptive control method for the attitude tracking control problem of spacecraft with inertia uncertainties. The proposed immersion and invariance (I&I) based adaptation law provides a more direct and flexible approach to circumvent the limitations of the basic I&I method without employing any filter signal. By virtue of the adaptation high-gain equivalence property derived from the proposed adaptive method, the closed-loop adaptive system with a low adaptation gain could recover the high adaptation gain performance of the filter-based I&I method, and the resulting control torque demands during the initial transient has been significantly reduced. A special feature of this method is that the convergence of the parameter estimation error has been observably improved by utilizing an adaptation gain matrix instead of a single adaptation gain value. Numerical simulations are presented to highlight the various benefits of the proposed method compared with the certainty-equivalence-based control method and filter-based I&I control schemes.

The life cycles of six multi-center adaptive clinical trials focused on neurological emergencies developed for the Advancing Regulatory Science initiative of the National Institutes of Health and US Food and Drug Administration: Case studies from the Adaptive Designs Accelerating Promising Treatments Into Trials Project.

PubMed

Guetterman, Timothy C; Fetters, Michael D; Mawocha, Samkeliso; Legocki, Laurie J; Barsan, William G; Lewis, Roger J; Berry, Donald A; Meurer, William J

2017-01-01

Clinical trials are complicated, expensive, time-consuming, and frequently do not lead to discoveries that improve the health of patients with disease. Adaptive clinical trials have emerged as a methodology to provide more flexibility in design elements to better answer scientific questions regarding whether new treatments are efficacious. Limited observational data exist that describe the complex process of designing adaptive clinical trials. To address these issues, the Adaptive Designs Accelerating Promising Treatments Into Trials project developed six, tailored, flexible, adaptive, phase-III clinical trials for neurological emergencies, and investigators prospectively monitored and observed the processes. The objective of this work is to describe the adaptive design development process, the final design, and the current status of the adaptive trial designs that were developed. To observe and reflect upon the trial development process, we employed a rich, mixed methods evaluation that combined quantitative data from visual analog scale to assess attitudes about adaptive trials, along with in-depth qualitative data about the development process gathered from observations. The Adaptive Designs Accelerating Promising Treatments Into Trials team developed six adaptive clinical trial designs. Across the six designs, 53 attitude surveys were completed at baseline and after the trial planning process completed. Compared to baseline, the participants believed significantly more strongly that the adaptive designs would be accepted by National Institutes of Health review panels and non-researcher clinicians. In addition, after the trial planning process, the participants more strongly believed that the adaptive design would meet the scientific and medical goals of the studies. Introducing the adaptive design at early conceptualization proved critical to successful adoption and implementation of that trial. Involving key stakeholders from several scientific domains early in the process appears to be associated with improved attitudes towards adaptive designs over the life cycle of clinical trial development.

Reflections on the Adaptive Designs Accelerating Promising Trials Into Treatments (ADAPT-IT) Process—Findings from a Qualitative Study

PubMed Central

Guetterman, Timothy C.; Fetters, Michael D.; Legocki, Laurie J.; Mawocha, Samkeliso; Barsan, William G.; Lewis, Roger J.; Berry, Donald A.; Meurer, William J.

2015-01-01

Context The context for this study was the Adaptive Designs Advancing Promising Treatments Into Trials (ADAPT-IT) project, which aimed to incorporate flexible adaptive designs into pivotal clinical trials and to conduct an assessment of the trial development process. Little research provides guidance to academic institutions in planning adaptive trials. Objectives The purpose of this qualitative study was to explore the perspectives and experiences of stakeholders as they reflected back about the interactive ADAPT-IT adaptive design development process, and to understand their perspectives regarding lessons learned about the design of the trials and trial development. Materials and methods We conducted semi-structured interviews with ten key stakeholders and observations of the process. We employed qualitative thematic text data analysis to reduce the data into themes about the ADAPT-IT project and adaptive clinical trials. Results The qualitative analysis revealed four themes: education of the project participants, how the process evolved with participant feedback, procedures that could enhance the development of other trials, and education of the broader research community. Discussion and conclusions While participants became more likely to consider flexible adaptive designs, additional education is needed to both understand the adaptive methodology and articulate it when planning trials. PMID:26622163

Biomimetic molecular design tools that learn, evolve, and adapt.

PubMed

Winkler, David A

2017-01-01

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known "S curve", with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

Biomimetic molecular design tools that learn, evolve, and adapt

PubMed Central

2017-01-01

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

Adaptive nonlinear control for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Black, William S.

We present the background and motivation for ground vehicle autonomy, and focus on uses for space-exploration. Using a simple design example of an autonomous ground vehicle we derive the equations of motion. After providing the mathematical background for nonlinear systems and control we present two common methods for exactly linearizing nonlinear systems, feedback linearization and backstepping. We use these in combination with three adaptive control methods: model reference adaptive control, adaptive sliding mode control, and extremum-seeking model reference adaptive control. We show the performances of each combination through several simulation results. We then consider disturbances in the system, and design nonlinear disturbance observers for both single-input-single-output and multi-input-multi-output systems. Finally, we show the performance of these observers with simulation results.

Practical characteristics of adaptive design in phase 2 and 3 clinical trials.

PubMed

Sato, A; Shimura, M; Gosho, M

2018-04-01

Adaptive design methods are expected to be ethical, reflect real medical practice, increase the likelihood of research and development success and reduce the allocation of patients into ineffective treatment groups by the early termination of clinical trials. However, the comprehensive details regarding which types of clinical trials will include adaptive designs remain unclear. We examined the practical characteristics of adaptive design used in clinical trials. We conducted a literature search of adaptive design clinical trials published from 2012 to 2015 using PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials, with common search terms related to adaptive design. We systematically assessed the types and characteristics of adaptive designs and disease areas employed in the adaptive design trials. Our survey identified 245 adaptive design clinical trials. The number of trials by the publication year increased from 2012 to 2013 and did not greatly change afterwards. The most frequently used adaptive design was group sequential design (n = 222, 90.6%), especially for neoplasm or cardiovascular disease trials. Among the other types of adaptive design, adaptive dose/treatment group selection (n = 21, 8.6%) and adaptive sample-size adjustment (n = 19, 7.8%) were frequently used. The adaptive randomization (n = 8, 3.3%) and adaptive seamless design (n = 6, 2.4%) were less frequent. Adaptive dose/treatment group selection and adaptive sample-size adjustment were frequently used (up to 23%) in "certain infectious and parasitic diseases," "diseases of nervous system," and "mental and behavioural disorders" in comparison with "neoplasms" (<6.6%). For "mental and behavioural disorders," adaptive randomization was used in two trials of eight trials in total (25%). Group sequential design and adaptive sample-size adjustment were used frequently in phase 3 trials or in trials where study phase was not specified, whereas the other types of adaptive designs were used more in phase 2 trials. Approximately 82% (202 of 245 trials) resulted in early termination at the interim analysis. Among the 202 trials, 132 (54% of 245 trials) had fewer randomized patients than initially planned. This result supports the motive to use adaptive design to make study durations shorter and include a smaller number of subjects. We found that adaptive designs have been applied to clinical trials in various therapeutic areas and interventions. The applications were frequently reported in neoplasm or cardiovascular clinical trials. The adaptive dose/treatment group selection and sample-size adjustment are increasingly common, and these adaptations generally follow the Food and Drug Administration's (FDA's) recommendations. © 2017 John Wiley & Sons Ltd.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

Using Bayesian Adaptive Trial Designs for Comparative Effectiveness Research: A Virtual Trial Execution.

PubMed

Luce, Bryan R; Connor, Jason T; Broglio, Kristine R; Mullins, C Daniel; Ishak, K Jack; Saunders, Elijah; Davis, Barry R

2016-09-20

Bayesian and adaptive clinical trial designs offer the potential for more efficient processes that result in lower sample sizes and shorter trial durations than traditional designs. To explore the use and potential benefits of Bayesian adaptive clinical trial designs in comparative effectiveness research. Virtual execution of ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) as if it had been done according to a Bayesian adaptive trial design. Comparative effectiveness trial of antihypertensive medications. Patient data sampled from the more than 42 000 patients enrolled in ALLHAT with publicly available data. Number of patients randomly assigned between groups, trial duration, observed numbers of events, and overall trial results and conclusions. The Bayesian adaptive approach and original design yielded similar overall trial conclusions. The Bayesian adaptive trial randomly assigned more patients to the better-performing group and would probably have ended slightly earlier. This virtual trial execution required limited resampling of ALLHAT patients for inclusion in RE-ADAPT (REsearch in ADAptive methods for Pragmatic Trials). Involvement of a data monitoring committee and other trial logistics were not considered. In a comparative effectiveness research trial, Bayesian adaptive trial designs are a feasible approach and potentially generate earlier results and allocate more patients to better-performing groups. National Heart, Lung, and Blood Institute.

Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

PubMed Central

Antoniou, Miranta; Jorgensen, Andrea L; Kolamunnage-Dona, Ruwanthi

2016-01-01

Background Personalized medicine is a growing area of research which aims to tailor the treatment given to a patient according to one or more personal characteristics. These characteristics can be demographic such as age or gender, or biological such as a genetic or other biomarker. Prior to utilizing a patient’s biomarker information in clinical practice, robust testing in terms of analytical validity, clinical validity and clinical utility is necessary. A number of clinical trial designs have been proposed for testing a biomarker’s clinical utility, including Phase II and Phase III clinical trials which aim to test the effectiveness of a biomarker-guided approach to treatment; these designs can be broadly classified into adaptive and non-adaptive. While adaptive designs allow planned modifications based on accumulating information during a trial, non-adaptive designs are typically simpler but less flexible. Methods and Findings We have undertaken a comprehensive review of biomarker-guided adaptive trial designs proposed in the past decade. We have identified eight distinct biomarker-guided adaptive designs and nine variations from 107 studies. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. We have graphically displayed the current biomarker-guided adaptive trial designs and summarised the characteristics of each design. Conclusions Our in-depth overview provides future researchers with clarity in definition, methodology and terminology for biomarker-guided adaptive trial designs. PMID:26910238

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

NASA Astrophysics Data System (ADS)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

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.

Adaptive web sampling.

PubMed

Thompson, Steven K

2006-12-01

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

Experimental Design and Primary Data Analysis Methods for Comparing Adaptive Interventions

PubMed Central

Nahum-Shani, Inbal; Qian, Min; Almirall, Daniel; Pelham, William E.; Gnagy, Beth; Fabiano, Greg; Waxmonsky, Jim; Yu, Jihnhee; Murphy, Susan

2013-01-01

In recent years, research in the area of intervention development is shifting from the traditional fixed-intervention approach to adaptive interventions, which allow greater individualization and adaptation of intervention options (i.e., intervention type and/or dosage) over time. Adaptive interventions are operationalized via a sequence of decision rules that specify how intervention options should be adapted to an individual’s characteristics and changing needs, with the general aim to optimize the long-term effectiveness of the intervention. Here, we review adaptive interventions, discussing the potential contribution of this concept to research in the behavioral and social sciences. We then propose the sequential multiple assignment randomized trial (SMART), an experimental design useful for addressing research questions that inform the construction of high-quality adaptive interventions. To clarify the SMART approach and its advantages, we compare SMART with other experimental approaches. We also provide methods for analyzing data from SMART to address primary research questions that inform the construction of a high-quality adaptive intervention. PMID:23025433

Drought Adaptation Mechanisms Should Guide Experimental Design.

PubMed

Gilbert, Matthew E; Medina, Viviana

2016-08-01

The mechanism, or hypothesis, of how a plant might be adapted to drought should strongly influence experimental design. For instance, an experiment testing for water conservation should be distinct from a damage-tolerance evaluation. We define here four new, general mechanisms for plant adaptation to drought such that experiments can be more easily designed based upon the definitions. A series of experimental methods are suggested together with appropriate physiological measurements related to the drought adaptation mechanisms. The suggestion is made that the experimental manipulation should match the rate, length, and severity of soil water deficit (SWD) necessary to test the hypothesized type of drought adaptation mechanism. Copyright © 2016 Elsevier Ltd. All rights reserved.

Implementation of time-efficient adaptive sampling function design for improved undersampled MRI reconstruction

NASA Astrophysics Data System (ADS)

Choi, Jinhyeok; Kim, Hyeonjin

2016-12-01

To improve the efficacy of undersampled MRI, a method of designing adaptive sampling functions is proposed that is simple to implement on an MR scanner and yet effectively improves the performance of the sampling functions. An approximation of the energy distribution of an image (E-map) is estimated from highly undersampled k-space data acquired in a prescan and efficiently recycled in the main scan. An adaptive probability density function (PDF) is generated by combining the E-map with a modeled PDF. A set of candidate sampling functions are then prepared from the adaptive PDF, among which the one with maximum energy is selected as the final sampling function. To validate its computational efficiency, the proposed method was implemented on an MR scanner, and its robust performance in Fourier-transform (FT) MRI and compressed sensing (CS) MRI was tested by simulations and in a cherry tomato. The proposed method consistently outperforms the conventional modeled PDF approach for undersampling ratios of 0.2 or higher in both FT-MRI and CS-MRI. To fully benefit from undersampled MRI, it is preferable that the design of adaptive sampling functions be performed online immediately before the main scan. In this way, the proposed method may further improve the efficacy of the undersampled MRI.

Procedures for Computing Transonic Flows for Control of Adaptive Wind Tunnels. Ph.D. Thesis - Technische Univ., Berlin, Mar. 1986

NASA Technical Reports Server (NTRS)

Rebstock, Rainer

1987-01-01

Numerical methods are developed for control of three dimensional adaptive test sections. The physical properties of the design problem occurring in the external field computation are analyzed, and a design procedure suited for solution of the problem is worked out. To do this, the desired wall shape is determined by stepwise modification of an initial contour. The necessary changes in geometry are determined with the aid of a panel procedure, or, with incident flow near the sonic range, with a transonic small perturbation (TSP) procedure. The designed wall shape, together with the wall deflections set during the tunnel run, are the input to a newly derived one-step formula which immediately yields the adapted wall contour. This is particularly important since the classical iterative adaptation scheme is shown to converge poorly for 3D flows. Experimental results obtained in the adaptive test section with eight flexible walls are presented to demonstrate the potential of the procedure. Finally, a method is described to minimize wall interference in 3D flows by adapting only the top and bottom wind tunnel walls.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

Lindorff, D. P.; Carroll, R. L.

1973-01-01

A survey of the literature in which Liapunov's second method is used in determining the control law is presented, with emphasis placed on the model-tracking adaptive control problem. Forty references are listed. Following a brief tutorial exposition of the adaptive control problem, the techniques for treating reduction of order, disturbance and time-varying parameters, multivariable systems, identification, and adaptive observers are discussed. The method is critically evaluated, particularly with respect to possibilities for application.

Obtaining the Optimal Dose in Alcohol Dependence Studies

PubMed Central

Wages, Nolan A.; Liu, Lei; O’Quigley, John; Johnson, Bankole A.

2012-01-01

In alcohol dependence studies, the treatment effect at different dose levels remains to be ascertained. Establishing this effect would aid us in identifying the best dose that has satisfactory efficacy while minimizing the rate of adverse events. We advocate the use of dose-finding methodology that has been successfully implemented in the cancer and HIV settings to identify the optimal dose in a cost-effective way. Specifically, we describe the continual reassessment method (CRM), an adaptive design proposed for cancer trials to reconcile the needs of dose-finding experiments with the ethical demands of established medical practice. We are applying adaptive designs for identifying the optimal dose of medications for the first time in the context of pharmacotherapy research in alcoholism. We provide an example of a topiramate trial as an illustration of how adaptive designs can be used to locate the optimal dose in alcohol treatment trials. It is believed that the introduction of adaptive design methods will enable the development of medications for the treatment of alcohol dependence to be accelerated. PMID:23189064

An Adaptive Cross-Architecture Combination Method for Graph Traversal

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

You, Yang; Song, Shuaiwen; Kerbyson, Darren J.

2014-06-18

Breadth-First Search (BFS) is widely used in many real-world applications including computational biology, social networks, and electronic design automation. The combination method, using both top-down and bottom-up techniques, is the most effective BFS approach. However, current combination methods rely on trial-and-error and exhaustive search to locate the optimal switching point, which may cause significant runtime overhead. To solve this problem, we design an adaptive method based on regression analysis to predict an optimal switching point for the combination method at runtime within less than 0.1% of the BFS execution time.

State of the art in adaptive control of robotic systems

NASA Technical Reports Server (NTRS)

Tosunoglu, Sabri; Tesar, Delbert

1988-01-01

An up-to-date assessment of adaptive control technology as applied to robotics is presented. Although the field is relatively new and does not yet represent a mature discipline, considerable attention for the design of sophisticated robot controllers has occured. In this presentation, 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.

Trends in study design and the statistical methods employed in a leading general medicine journal.

PubMed

Gosho, M; Sato, Y; Nagashima, K; Takahashi, S

2018-02-01

Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design. © 2017 John Wiley & Sons Ltd.

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.

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Application of positive-real functions in hyperstable discrete model-reference adaptive system design.

NASA Technical Reports Server (NTRS)

Karmarkar, J. S.

1972-01-01

Proposal of an algorithmic procedure, based on mathematical programming methods, to design compensators for hyperstable discrete model-reference adaptive systems (MRAS). The objective of the compensator is to render the MRAS insensitive to initial parameter estimates within a maximized hypercube in the model parameter space.

Artificial Intelligence Methods in Computer-Based Instructional Design. The Minnesota Adaptive Instructional System.

ERIC Educational Resources Information Center

Tennyson, Robert

1984-01-01

Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…

78 FR 77646 - Proposed Information Collection; Comment Request; 2014 Census Site Test

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-24

... pre-notification containing instructions about how to respond to the test online. Some households will... Adaptive Design Strategies portion will test a method of managing data collection by dynamically adapting... methodology. The objectives of this component of the test are to: Design and develop software solutions...

Using mixed methods research designs in health psychology: an illustrated discussion from a pragmatist perspective.

PubMed

Bishop, Felicity L

2015-02-01

To outline some of the challenges of mixed methods research and illustrate how they can be addressed in health psychology research. This study critically reflects on the author's previously published mixed methods research and discusses the philosophical and technical challenges of mixed methods, grounding the discussion in a brief review of methodological literature. Mixed methods research is characterized as having philosophical and technical challenges; the former can be addressed by drawing on pragmatism, the latter by considering formal mixed methods research designs proposed in a number of design typologies. There are important differences among the design typologies which provide diverse examples of designs that health psychologists can adapt for their own mixed methods research. There are also similarities; in particular, many typologies explicitly orient to the technical challenges of deciding on the respective timing of qualitative and quantitative methods and the relative emphasis placed on each method. Characteristics, strengths, and limitations of different sequential and concurrent designs are identified by reviewing five mixed methods projects each conducted for a different purpose. Adapting formal mixed methods designs can help health psychologists address the technical challenges of mixed methods research and identify the approach that best fits the research questions and purpose. This does not obfuscate the need to address philosophical challenges of mixing qualitative and quantitative methods. Statement of contribution What is already known on this subject? Mixed methods research poses philosophical and technical challenges. Pragmatism in a popular approach to the philosophical challenges while diverse typologies of mixed methods designs can help address the technical challenges. Examples of mixed methods research can be hard to locate when component studies from mixed methods projects are published separately. What does this study add? Critical reflections on the author's previously published mixed methods research illustrate how a range of different mixed methods designs can be adapted and applied to address health psychology research questions. The philosophical and technical challenges of mixed methods research should be considered together and in relation to the broader purpose of the research. © 2014 The British Psychological Society.

Design of sewage treatment system by applying fuzzy adaptive PID controller

NASA Astrophysics Data System (ADS)

Jin, Liang-Ping; Li, Hong-Chan

2013-03-01

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

ERIC Educational Resources Information Center

du Plessis, Santie

2015-01-01

The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.

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.

Adaptive seamless designs: selection and prospective testing of hypotheses.

PubMed

Jennison, Christopher; Turnbull, Bruce W

2007-01-01

There is a current trend towards clinical protocols which involve an initial "selection" phase followed by a hypothesis testing phase. The selection phase may involve a choice between competing treatments or different dose levels of a drug, between different target populations, between different endpoints, or between a superiority and a non-inferiority hypothesis. Clearly there can be benefits in elapsed time and economy in organizational effort if both phases can be designed up front as one experiment, with little downtime between phases. Adaptive designs have been proposed as a way to handle these selection/testing problems. They offer flexibility and allow final inferences to depend on data from both phases, while maintaining control of overall false positive rates. We review and critique the methods, give worked examples and discuss the efficiency of adaptive designs relative to more conventional procedures. Where gains are possible using the adaptive approach, a variety of logistical, operational, data handling and other practical difficulties remain to be overcome if adaptive, seamless designs are to be effectively implemented.

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Topological Methods for Design and Control of Adaptive Stochastic Complex Systems - to Meet the Challenges of Resilient Urban Infrastructure

DTIC Science & Technology

2017-03-24

for Design and Control of Adaptive Stochastic Complex Systems John Baillieul∗ Contents 1 Executive Summary 2 2 Introduction and Issues to Be Addressed...difficult of real-world Systems-of-Systems challenges is the design and operational control of medical treatment networks that support forces operating...This report describes a brief research project on foundartional aspects of systems-of-systems design and operation. The overarching goal of the

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

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.

Optimization of cold-adapted lysozyme production from the psychrophilic yeast Debaryomyces hansenii using statistical experimental methods.

PubMed

Wang, Quanfu; Hou, Yanhua; Yan, Peisheng

2012-06-01

Statistical experimental designs were employed to optimize culture conditions for cold-adapted lysozyme production of a psychrophilic yeast Debaryomyces hansenii. In the first step of optimization using Plackett-Burman design (PBD), peptone, glucose, temperature, and NaCl were identified as significant variables that affected lysozyme production, the formula was further optimized using a four factor central composite design (CCD) to understand their interaction and to determine their optimal levels. A quadratic model was developed and validated. Compared to the initial level (18.8 U/mL), the maximum lysozyme production (65.8 U/mL) observed was approximately increased by 3.5-fold under the optimized conditions. Cold-adapted lysozymes production was first optimized using statistical experimental methods. A 3.5-fold enhancement of microbial lysozyme was gained after optimization. Such an improved production will facilitate the application of microbial lysozyme. Thus, D. hansenii lysozyme may be a good and new resource for the industrial production of cold-adapted lysozymes. © 2012 Institute of Food Technologists®

Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

PubMed

Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

2013-12-01

Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Using diagnostic experiences in experience-based innovative design

NASA Astrophysics Data System (ADS)

Prabhakar, Sattiraju; Goel, Ashok K.

1992-03-01

Designing a novel class of devices requires innovation. Often, the design knowledge of these devices does not identify and address the constraints that are required for their performance in the real world operating environment. So any new design adapted from these devices tend to be similarly sketchy. In order to address this problem, we propose a case-based reasoning method called performance driven innovation (PDI). We model the design as a dynamic process, arrive at a design by adaptation from the known designs, generate failures for this design for some new constraints, and then use this failure knowledge to generate the required design knowledge for the new constraints. In this paper, we discuss two aspects of PDI: the representation of PDI cases and the translation of the failure knowledge into design knowledge for a constraint. Each case in PDI has two components: design and failure knowledge. Both of them are represented using a substance-behavior-function model. Failure knowledge has internal device failure behaviors and external environmental behaviors. The environmental behavior, for a constraint, interacting with the design behaviors, results in the failure internal behavior. The failure adaptation strategy generates functions, from the failure knowledge, which can be addressed using the routine design methods. These ideas are illustrated using a coffee-maker example.

Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm

NASA Astrophysics Data System (ADS)

Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui

2017-05-01

The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.

Anti-windup adaptive PID control design for a class of uncertain chaotic systems with input saturation.

PubMed

Tahoun, A H

2017-01-01

In this paper, the stabilization problem of actuators saturation in uncertain chaotic systems is investigated via an adaptive PID control method. The PID control parameters are auto-tuned adaptively via adaptive control laws. A multi-level augmented error is designed to account for the extra terms appearing due to the use of PID and saturation. The proposed control technique uses both the state-feedback and the output-feedback methodologies. Based on Lyapunov׳s stability theory, new anti-windup adaptive controllers are proposed. Demonstrative examples with MATLAB simulations are studied. The simulation results show the efficiency of the proposed adaptive PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Participatory Design of Mass Health Communication in Three Languages for Seniors and People With Disabilities on Medicaid

PubMed Central

Rothschild, Beccah; Graham, Carrie; Ivey, Susan L.; Konishi, Susana

2009-01-01

Objectives. We used participatory design methods to develop and test guidebooks about health care choices intended for 600 000 English-, Spanish-, and Chinese-speaking seniors and people with disabilities receiving Medicaid in California. Methods. Design and testing processes were conducted with consumers and professionals; they included 24 advisory group interviews, 36 usability tests, 18 focus groups (105 participants), 51 key informant interviews, guidebook readability and suitability testing, linguistic adaptation, and iterative revisions of 4 prototypes. Results. Participatory design processes identified preferences of intended audiences for guidebook content, linguistic adaptation, and format; guidebook readability was scored at the sixth- to eighth-grade level and suitability at 95%. These findings informed the design of a separate efficacy study that showed high guidebook usage and satisfaction, and better gains in knowledge, confidence, and intended behaviors among intervention participants than among control participants. Conclusions. Participatory design can be used effectively in mass communication to inform vulnerable audiences of health care choices. The techniques described can be adapted for a broad range of health communication interventions. PMID:19833990

Adaptive sampling in behavioral surveys.

PubMed

Thompson, S K

1997-01-01

Studies of populations such as drug users encounter difficulties because the members of the populations are rare, hidden, or hard to reach. Conventionally designed large-scale surveys detect relatively few members of the populations so that estimates of population characteristics have high uncertainty. Ethnographic studies, on the other hand, reach suitable numbers of individuals only through the use of link-tracing, chain referral, or snowball sampling procedures that often leave the investigators unable to make inferences from their sample to the hidden population as a whole. In adaptive sampling, the procedure for selecting people or other units to be in the sample depends on variables of interest observed during the survey, so the design adapts to the population as encountered. For example, when self-reported drug use is found among members of the sample, sampling effort may be increased in nearby areas. Types of adaptive sampling designs include ordinary sequential sampling, adaptive allocation in stratified sampling, adaptive cluster sampling, and optimal model-based designs. Graph sampling refers to situations with nodes (for example, people) connected by edges (such as social links or geographic proximity). An initial sample of nodes or edges is selected and edges are subsequently followed to bring other nodes into the sample. Graph sampling designs include network sampling, snowball sampling, link-tracing, chain referral, and adaptive cluster sampling. A graph sampling design is adaptive if the decision to include linked nodes depends on variables of interest observed on nodes already in the sample. Adjustment methods for nonsampling errors such as imperfect detection of drug users in the sample apply to adaptive as well as conventional designs.

In-Flight System Identification

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1998-01-01

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Improved methods in neural network-based adaptive output feedback control, with applications to flight control

NASA Astrophysics Data System (ADS)

Kim, Nakwan

Utilizing the universal approximation property of neural networks, we develop several novel approaches to neural network-based adaptive output feedback control of nonlinear systems, and illustrate these approaches for several flight control applications. In particular, we address the problem of non-affine systems and eliminate the fixed point assumption present in earlier work. All of the stability proofs are carried out in a form that eliminates an algebraic loop in the neural network implementation. An approximate input/output feedback linearizing controller is augmented with a neural network using input/output sequences of the uncertain system. These approaches permit adaptation to both parametric uncertainty and unmodeled dynamics. All physical systems also have control position and rate limits, which may either deteriorate performance or cause instability for a sufficiently high control bandwidth. Here we apply a method for protecting an adaptive process from the effects of input saturation and time delays, known as "pseudo control hedging". This method was originally developed for the state feedback case, and we provide a stability analysis that extends its domain of applicability to the case of output feedback. The approach is illustrated by the design of a pitch-attitude flight control system for a linearized model of an R-50 experimental helicopter, and by the design of a pitch-rate control system for a 58-state model of a flexible aircraft consisting of rigid body dynamics coupled with actuator and flexible modes. A new approach to augmentation of an existing linear controller is introduced. It is especially useful when there is limited information concerning the plant model, and the existing controller. The approach is applied to the design of an adaptive autopilot for a guided munition. Design of a neural network adaptive control that ensures asymptotically stable tracking performance is also addressed.

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

NASA Technical Reports Server (NTRS)

Burken, John J.

2005-01-01

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

Mixed Methods in Intervention Research: Theory to Adaptation

ERIC Educational Resources Information Center

Nastasi, Bonnie K.; Hitchcock, John; Sarkar, Sreeroopa; Burkholder, Gary; Varjas, Kristen; Jayasena, Asoka

2007-01-01

The purpose of this article is to demonstrate the application of mixed methods research designs to multiyear programmatic research and development projects whose goals include integration of cultural specificity when generating or translating evidence-based practices. The authors propose a set of five mixed methods designs related to different…

Irregular and adaptive sampling for automatic geophysic measure systems

NASA Astrophysics Data System (ADS)

Avagnina, Davide; Lo Presti, Letizia; Mulassano, Paolo

2000-07-01

In this paper a sampling method, based on an irregular and adaptive strategy, is described. It can be used as automatic guide for rovers designed to explore terrestrial and planetary environments. Starting from the hypothesis that a explorative vehicle is equipped with a payload able to acquire measurements of interesting quantities, the method is able to detect objects of interest from measured points and to realize an adaptive sampling, while badly describing the not interesting background.

Final Report - Regulatory Considerations for Adaptive Systems

NASA Technical Reports Server (NTRS)

Wilkinson, Chris; Lynch, Jonathan; Bharadwaj, Raj

2013-01-01

This report documents the findings of a preliminary research study into new approaches to the software design assurance of adaptive systems. We suggest a methodology to overcome the software validation and verification difficulties posed by the underlying assumption of non-adaptive software in the requirementsbased- testing verification methods in RTCA/DO-178B and C. An analysis of the relevant RTCA/DO-178B and C objectives is presented showing the reasons for the difficulties that arise in showing satisfaction of the objectives and suggested additional means by which they could be satisfied. We suggest that the software design assurance problem for adaptive systems is principally one of developing correct and complete high level requirements and system level constraints that define the necessary system functional and safety properties to assure the safe use of adaptive systems. We show how analytical techniques such as model based design, mathematical modeling and formal or formal-like methods can be used to both validate the high level functional and safety requirements, establish necessary constraints and provide the verification evidence for the satisfaction of requirements and constraints that supplements conventional testing. Finally the report identifies the follow-on research topics needed to implement this methodology.

Adaptive Backstepping-Based Neural Tracking Control for MIMO Nonlinear Switched Systems Subject to Input Delays.

PubMed

Niu, Ben; Li, Lu

2018-06-01

This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.

Experimental verification of a real-time tuning method of a model-based controller by perturbations to its poles

NASA Astrophysics Data System (ADS)

Kajiwara, Itsuro; Furuya, Keiichiro; Ishizuka, Shinichi

2018-07-01

Model-based controllers with adaptive design variables are often used to control an object with time-dependent characteristics. However, the controller's performance is influenced by many factors such as modeling accuracy and fluctuations in the object's characteristics. One method to overcome these negative factors is to tune model-based controllers. Herein we propose an online tuning method to maintain control performance for an object that exhibits time-dependent variations. The proposed method employs the poles of the controller as design variables because the poles significantly impact performance. Specifically, we use the simultaneous perturbation stochastic approximation (SPSA) to optimize a model-based controller with multiple design variables. Moreover, a vibration control experiment of an object with time-dependent characteristics as the temperature is varied demonstrates that the proposed method allows adaptive control and stably maintains the closed-loop characteristics.

LMI-based adaptive reliable H∞ static output feedback control against switched actuator failures

NASA Astrophysics Data System (ADS)

An, Liwei; Zhai, Ding; Dong, Jiuxiang; Zhang, Qingling

2017-08-01

This paper investigates the H∞ static output feedback (SOF) control problem for switched linear system under arbitrary switching, where the actuator failure models are considered to depend on switching signal. An active reliable control scheme is developed by combination of linear matrix inequality (LMI) method and adaptive mechanism. First, by exploiting variable substitution and Finsler's lemma, new LMI conditions are given for designing the SOF controller. Compared to the existing results, the proposed design conditions are more relaxed and can be applied to a wider class of no-fault linear systems. Then a novel adaptive mechanism is established, where the inverses of switched failure scaling factors are estimated online to accommodate the effects of actuator failure on systems. Two main difficulties arise: first is how to design the switched adaptive laws to prevent the missing of estimating information due to switching; second is how to construct a common Lyapunov function based on a switched estimate error term. It is shown that the new method can give less conservative results than that for the traditional control design with fixed gain matrices. Finally, simulation results on the HiMAT aircraft are given to show the effectiveness of the proposed approaches.

User Interface Design in Medical Distributed Web Applications.

PubMed

Serban, Alexandru; Crisan-Vida, Mihaela; Mada, Leonard; Stoicu-Tivadar, Lacramioara

2016-01-01

User interfaces are important to facilitate easy learning and operating with an IT application especially in the medical world. An easy to use interface has to be simple and to customize the user needs and mode of operation. The technology in the background is an important tool to accomplish this. The present work aims to creating a web interface using specific technology (HTML table design combined with CSS3) to provide an optimized responsive interface for a complex web application. In the first phase, the current icMED web medical application layout is analyzed, and its structure is designed using specific tools, on source files. In the second phase, a new graphic adaptable interface to different mobile terminals is proposed, (using HTML table design (TD) and CSS3 method) that uses no source files, just lines of code for layout design, improving the interaction in terms of speed and simplicity. For a complex medical software application a new prototype layout was designed and developed using HTML tables. The method uses a CSS code with only CSS classes applied to one or multiple HTML table elements, instead of CSS styles that can be applied to just one DIV tag at once. The technique has the advantage of a simplified CSS code, and a better adaptability to different media resolutions compared to DIV-CSS style method. The presented work is a proof that adaptive web interfaces can be developed just using and combining different types of design methods and technologies, using HTML table design, resulting in a simpler to learn and use interface, suitable for healthcare services.

Power of an Adaptive Trial Design for Endovascular Stroke Studies: Simulations Using IMS (Interventional Management of Stroke) III Data.

PubMed

Lansberg, Maarten G; Bhat, Ninad S; Yeatts, Sharon D; Palesch, Yuko Y; Broderick, Joseph P; Albers, Gregory W; Lai, Tze L; Lavori, Philip W

2016-12-01

Adaptive trial designs that allow enrichment of the study population through subgroup selection can increase the chance of a positive trial when there is a differential treatment effect among patient subgroups. The goal of this study is to illustrate the potential benefit of adaptive subgroup selection in endovascular stroke studies. We simulated the performance of a trial design with adaptive subgroup selection and compared it with that of a traditional design. Outcome data were based on 90-day modified Rankin Scale scores, observed in IMS III (Interventional Management of Stroke III), among patients with a vessel occlusion on baseline computed tomographic angiography (n=382). Patients were categorized based on 2 methods: (1) according to location of the arterial occlusive lesion and onset-to-randomization time and (2) according to onset-to-randomization time alone. The power to demonstrate a treatment benefit was based on 10 000 trial simulations for each design. The treatment effect was relatively homogeneous across categories when patients were categorized based on arterial occlusive lesion and time. Consequently, the adaptive design had similar power (47%) compared with the fixed trial design (45%). There was a differential treatment effect when patients were categorized based on time alone, resulting in greater power with the adaptive design (82%) than with the fixed design (57%). These simulations, based on real-world patient data, indicate that adaptive subgroup selection has merit in endovascular stroke trials as it substantially increases power when the treatment effect differs among subgroups in a predicted pattern. © 2016 American Heart Association, Inc.

Beyond Reduction: Climate Change Adaptation Planning for Universities and Colleges

ERIC Educational Resources Information Center

Owen, Rochelle; Fisher, Erica; McKenzie, Kyle

2013-01-01

Purpose: The purpose of this paper is to outline a unique six-step process for the inclusion of climate change adaption goals and strategies in a University Climate Change Plan. Design/methodology/approach: A mixed-method approach was used to gather data on campus climate change vulnerabilities and adaption strategies. A literature review…

Principles and Methods of Adapted Physical Education and Recreation.

ERIC Educational Resources Information Center

Arnheim, Daniel D.; And Others

This text is designed for the elementary and secondary school physical educator and the recreation specialist in adapted physical education and, more specifically, as a text for college courses in adapted and corrective physical education and therapeutic recreation. The text is divided into four major divisions: scope, key teaching and therapy…

Team-Centered Perspective for Adaptive Automation Design

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III

2003-01-01

Automation represents a very active area of human factors research. The journal, Human Factors, published a special issue on automation in 1985. Since then, hundreds of scientific studies have been published examining the nature of automation and its interaction with human performance. However, despite a dramatic increase in research investigating human factors issues in aviation automation, there remain areas that need further exploration. This NASA Technical Memorandum describes a new area of automation design and research, called adaptive automation. It discusses the concepts and outlines the human factors issues associated with the new method of adaptive function allocation. The primary focus is on human-centered design, and specifically on ensuring that adaptive automation is from a team-centered perspective. The document shows that adaptive automation has many human factors issues common to traditional automation design. Much like the introduction of other new technologies and paradigm shifts, adaptive automation presents an opportunity to remediate current problems but poses new ones for human-automation interaction in aerospace operations. The review here is intended to communicate the philosophical perspective and direction of adaptive automation research conducted under the Aerospace Operations Systems (AOS), Physiological and Psychological Stressors and Factors (PPSF) project.

Adaptive control of servo system based on LuGre model

NASA Astrophysics Data System (ADS)

Jin, Wang; Niancong, Liu; Jianlong, Chen; Weitao, Geng

2018-03-01

This paper established a mechanical model of feed system based on LuGre model. In order to solve the influence of nonlinear factors on the system running stability, a nonlinear single observer is designed to estimate the parameter z in the LuGre model and an adaptive friction compensation controller is designed. Simulink simulation results show that the control method can effectively suppress the adverse effects of friction and external disturbances. The simulation show that the adaptive parameter kz is between 0.11-0.13, and the value of gamma1 is between 1.9-2.1. Position tracking error reaches level 10-3 and is stabilized near 0 values within 0.3 seconds, the compensation method has better tracking accuracy and robustness.

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.

Statistical controversies in clinical research: early-phase adaptive design for combination immunotherapies.

PubMed

Wages, N A; Slingluff, C L; Petroni, G R

2017-04-01

In recent years, investigators have asserted that the 3 + 3 design lacks flexibility, making its use in modern early-phase trial settings, such as combinations and/or biological agents, inefficient. More innovative approaches are required to address contemporary research questions, such as those posed in trials involving immunotherapies. We describe the implementation of an adaptive design for identifying an optimal treatment regimen, defined by low toxicity and high immune response, in an early-phase trial of a melanoma helper peptide vaccine plus novel adjuvant combinations. Operating characteristics demonstrate the ability of the method to effectively recommend optimal regimens in a high percentage of trials with reasonable sample sizes. The proposed design is a practical, early-phase, adaptive method for use with combined immunotherapy regimens. This design can be applied more broadly to early-phase combination studies, as it was used in an ongoing study of two small molecule inhibitors in relapsed/refractory mantle cell lymphoma. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

The Potential of Adaptive Design in Animal Studies.

PubMed

Majid, Arshad; Bae, Ok-Nam; Redgrave, Jessica; Teare, Dawn; Ali, Ali; Zemke, Daniel

2015-10-12

Clinical trials are the backbone of medical research, and are often the last step in the development of new therapies for use in patients. Prior to human testing, however, preclinical studies using animal subjects are usually performed in order to provide initial data on the safety and effectiveness of prospective treatments. These studies can be costly and time consuming, and may also raise concerns about the ethical treatment of animals when potentially harmful procedures are involved. Adaptive design is a process by which the methods used in a study may be altered while it is being conducted in response to preliminary data or other new information. Adaptive design has been shown to be useful in reducing the time and costs associated with clinical trials, and may provide similar benefits in preclinical animal studies. The purpose of this review is to summarize various aspects of adaptive design and evaluate its potential for use in preclinical research.

The Potential of Adaptive Design in Animal Studies

PubMed Central

Majid, Arshad; Bae, Ok-Nam; Redgrave, Jessica; Teare, Dawn; Ali, Ali; Zemke, Daniel

2015-01-01

Clinical trials are the backbone of medical research, and are often the last step in the development of new therapies for use in patients. Prior to human testing, however, preclinical studies using animal subjects are usually performed in order to provide initial data on the safety and effectiveness of prospective treatments. These studies can be costly and time consuming, and may also raise concerns about the ethical treatment of animals when potentially harmful procedures are involved. Adaptive design is a process by which the methods used in a study may be altered while it is being conducted in response to preliminary data or other new information. Adaptive design has been shown to be useful in reducing the time and costs associated with clinical trials, and may provide similar benefits in preclinical animal studies. The purpose of this review is to summarize various aspects of adaptive design and evaluate its potential for use in preclinical research. PMID:26473839

New adaptive method to optimize the secondary reflector of linear Fresnel collectors

DOE PAGES

Zhu, Guangdong

2017-01-16

Performance of linear Fresnel collectors may largely depend on the secondary-reflector profile design when small-aperture absorbers are used. Optimization of the secondary-reflector profile is an extremely challenging task because there is no established theory to ensure superior performance of derived profiles. In this work, an innovative optimization method is proposed to optimize the secondary-reflector profile of a generic linear Fresnel configuration. The method correctly and accurately captures impacts of both geometric and optical aspects of a linear Fresnel collector to secondary-reflector design. The proposed method is an adaptive approach that does not assume a secondary shape of any particular form,more » but rather, starts at a single edge point and adaptively constructs the next surface point to maximize the reflected power to be reflected to absorber(s). As a test case, the proposed optimization method is applied to an industrial linear Fresnel configuration, and the results show that the derived optimal secondary reflector is able to redirect more than 90% of the power to the absorber in a wide range of incidence angles. Here, the proposed method can be naturally extended to other types of solar collectors as well, and it will be a valuable tool for solar-collector designs with a secondary reflector.« less

New adaptive method to optimize the secondary reflector of linear Fresnel collectors

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

Zhu, Guangdong

Performance of linear Fresnel collectors may largely depend on the secondary-reflector profile design when small-aperture absorbers are used. Optimization of the secondary-reflector profile is an extremely challenging task because there is no established theory to ensure superior performance of derived profiles. In this work, an innovative optimization method is proposed to optimize the secondary-reflector profile of a generic linear Fresnel configuration. The method correctly and accurately captures impacts of both geometric and optical aspects of a linear Fresnel collector to secondary-reflector design. The proposed method is an adaptive approach that does not assume a secondary shape of any particular form,more » but rather, starts at a single edge point and adaptively constructs the next surface point to maximize the reflected power to be reflected to absorber(s). As a test case, the proposed optimization method is applied to an industrial linear Fresnel configuration, and the results show that the derived optimal secondary reflector is able to redirect more than 90% of the power to the absorber in a wide range of incidence angles. Here, the proposed method can be naturally extended to other types of solar collectors as well, and it will be a valuable tool for solar-collector designs with a secondary reflector.« less

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.

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

PubMed

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

2018-05-01

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

Adaptive Beam Loading Compensation in Room Temperature Bunching Cavities

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

Edelen, J. P.; Chase, B. E.; Cullerton, E.

In this paper we present the design, simulation, and proof of principle results of an optimization based adaptive feedforward algorithm for beam-loading compensation in a high impedance room temperature cavity. We begin with an overview of prior developments in beam loading compensation. Then we discuss different techniques for adaptive beam loading compensation and why the use of Newton?s Method is of interest for this application. This is followed by simulation and initial experimental results of this method.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

NASA Astrophysics Data System (ADS)

Xiao, Lingfei; Du, Yanbin; Hu, Jixiang; Jiang, Bin

2018-03-01

In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

Adaptive Prior Variance Calibration in the Bayesian Continual Reassessment Method

PubMed Central

Zhang, Jin; Braun, Thomas M.; Taylor, Jeremy M.G.

2012-01-01

Use of the Continual Reassessment Method (CRM) and other model-based approaches to design in Phase I clinical trials has increased due to the ability of the CRM to identify the maximum tolerated dose (MTD) better than the 3+3 method. However, the CRM can be sensitive to the variance selected for the prior distribution of the model parameter, especially when a small number of patients are enrolled. While methods have emerged to adaptively select skeletons and to calibrate the prior variance only at the beginning of a trial, there has not been any approach developed to adaptively calibrate the prior variance throughout a trial. We propose three systematic approaches to adaptively calibrate the prior variance during a trial and compare them via simulation to methods proposed to calibrate the variance at the beginning of a trial. PMID:22987660

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.

Providing Adaptation and Guidance for Design Learning by Problem Solving: The Design Planning Approach in DomoSim-TPC Environment

ERIC Educational Resources Information Center

Redondo, Miguel A.; Bravo, Crescencio; Ortega, Manuel; Verdejo, M. Felisa

2007-01-01

Experimental learning environments based on simulation usually require monitoring and adaptation to the actions the users carry out. Some systems provide this functionality, but they do so in a way which is static or cannot be applied to problem solving tasks. In response to this problem, we propose a method based on the use of intermediate…

A randomized controlled trial of culturally adapted motivational interviewing for Hispanic heavy drinkers: Theory of Adaptation and Study Protocol

PubMed Central

Lee, Christina S.; Colby, Suzanne M.; Magill, Molly; Almeida, Joanna; Tavares, Tonya; Rohsenow, Damaris J.

2016-01-01

Background The NIH Strategic Plan prioritizes health disparities research for socially disadvantaged Hispanics, to reduce the disproportionate burden of alcohol-related negative consequences compared to other racial/ethnic groups. Cultural adaptation of evidence-based treatments, such as motivational interviewing (MI), can improve access and response to alcohol treatment. However, the lack of rigorous clinical trials designed to test the efficacy and theoretical underpinnings of cultural adaptation has made proof of concept difficult. Objective The CAMI2 (Culturally Adapted Motivational Interviewing) study design and its theoretical model, is described to illustrate how MI adapted to social and cultural factors (CAMI) can be discriminated against non-adapted MI. Methods and Design CAMI2, a large, 12 month randomized prospective trial, examines the efficacy of CAMI and MI among heavy drinking Hispanics recruited from the community (n=257). Outcomes are reductions in heavy drinking days (Time Line Follow-Back) and negative consequences of drinking among Hispanics (Drinkers Inventory of Consequences). A second aim examines perceived acculturation stress as a moderator of treatment outcomes in the CAMI condition. Summary The CAMI2 study design protocol is presented and the theory of adaptation is presented. Findings from the trial described may yield important recommendations on the science of cultural adaptation and improve MI dissemination to Hispanics with alcohol risk. PMID:27565832

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Development of fault tolerant adaptive control laws for aerospace systems

NASA Astrophysics Data System (ADS)

Perez Rocha, Andres E.

The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.

Apparatus and method for handheld sampling

DOEpatents

Staab, Torsten A.

2005-09-20

The present invention includes an apparatus, and corresponding method, for taking a sample. The apparatus is built around a frame designed to be held in at least one hand. A sample media is used to secure the sample. A sample media adapter for securing the sample media is operated by a trigger mechanism connectively attached within the frame to the sample media adapter.

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate-Smart Design for Ecosystem Management: A Test Application for Coral Reefs.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Julius, Susan H; Hoffman, Jennie; Koltes, Karen H; MacGowan, Petra

2017-01-01

The interactive and cumulative impacts of climate change on natural resources such as coral reefs present numerous challenges for conservation planning and management. Climate change adaptation is complex due to climate-stressor interactions across multiple spatial and temporal scales. This leaves decision makers worldwide faced with local, regional, and global-scale threats to ecosystem processes and services, occurring over time frames that require both near-term and long-term planning. Thus there is a need for structured approaches to adaptation planning that integrate existing methods for vulnerability assessment with design and evaluation of effective adaptation responses. The Corals and Climate Adaptation Planning project of the U.S. Coral Reef Task Force seeks to develop guidance for improving coral reef management through tailored application of a climate-smart approach. This approach is based on principles from a recently-published guide which provides a framework for adopting forward-looking goals, based on assessing vulnerabilities to climate change and applying a structured process to design effective adaptation strategies. Work presented in this paper includes: (1) examination of the climate-smart management cycle as it relates to coral reefs; (2) a compilation of adaptation strategies for coral reefs drawn from a comprehensive review of the literature; (3) in-depth demonstration of climate-smart design for place-based crafting of robust adaptation actions; and (4) feedback from stakeholders on the perceived usefulness of the approach. We conclude with a discussion of lessons-learned on integrating climate-smart design into real-world management planning processes and a call from stakeholders for an "adaptation design tool" that is now under development.

Methodological Issues in Questionnaire Design.

PubMed

Song, Youngshin; Son, Youn Jung; Oh, Doonam

2015-06-01

The process of designing a questionnaire is complicated. Many questionnaires on nursing phenomena have been developed and used by nursing researchers. The purpose of this paper was to discuss questionnaire design and factors that should be considered when using existing scales. Methodological issues were discussed, such as factors in the design of questions, steps in developing questionnaires, wording and formatting methods for items, and administrations methods. How to use existing scales, how to facilitate cultural adaptation, and how to prevent socially desirable responding were discussed. Moreover, the triangulation method in questionnaire development was introduced. Steps were recommended for designing questions such as appropriately operationalizing key concepts for the target population, clearly formatting response options, generating items and confirming final items through face or content validity, sufficiently piloting the questionnaire using item analysis, demonstrating reliability and validity, finalizing the scale, and training the administrator. Psychometric properties and cultural equivalence should be evaluated prior to administration when using an existing questionnaire and performing cultural adaptation. In the context of well-defined nursing phenomena, logical and systematic methods will contribute to the development of simple and precise questionnaires.

Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

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

Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.

2015-01-01

Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combiningmore » the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.« less

Comparing oncology clinical programs by use of innovative designs and expected net present value optimization: Which adaptive approach leads to the best result?

PubMed

Parke, Tom; Marchenko, Olga; Anisimov, Vladimir; Ivanova, Anastasia; Jennison, Christopher; Perevozskaya, Inna; Song, Guochen

2017-01-01

Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected net present value (eNPV). In this article, we consider eight Phase2/Phase3 development programs based on selected combinations of five Phase 2 study designs and three Phase 3 study designs. We again used the probability of program success and eNPV to compare simulated programs. For the development strategies, we considered that the eNPV showed robust improvement for each successive strategy, with the highest being for a three-arm response adaptive randomization design in Phase 2 and a group sequential design with 5 analyses in Phase 3.

Development of a photogrammetric method of measuring tree taper outside bark

Treesearch

David R. Larsen

2006-01-01

A photogrammetric method is presented for measuring tree diameters outside bark using calibrated control ground-based digital photographs. The method was designed to rapidly collect tree taper information from subject trees for the development of tree taper equations. Software that is commercially available, but designed for a different purpose, can be readily adapted...

MindMatters--A Programme for the Promotion of Mental Health in Primary and Secondary Schools: Results of an Evaluation of the German Language Adaptation

ERIC Educational Resources Information Center

Franze, M.; Paulus, P.

2009-01-01

Purpose: The purpose of this article is to present a German adaptation of the Australian programme MindMatters for school mental health promotion in secondary schools. Design/methodology/approach: As well as other methods, the external evaluation consisted of a questionnaire-based pre-post-design (at one year interval of measurement; n=633…

Adaptive spline autoregression threshold method in forecasting Mitsubishi car sales volume at PT Srikandi Diamond Motors

NASA Astrophysics Data System (ADS)

Susanti, D.; Hartini, E.; Permana, A.

2017-01-01

Sale and purchase of the growing competition between companies in Indonesian, make every company should have a proper planning in order to win the competition with other companies. One of the things that can be done to design the plan is to make car sales forecast for the next few periods, it’s required that the amount of inventory of cars that will be sold in proportion to the number of cars needed. While to get the correct forecasting, on of the methods that can be used is the method of Adaptive Spline Threshold Autoregression (ASTAR). Therefore, this time the discussion will focus on the use of Adaptive Spline Threshold Autoregression (ASTAR) method in forecasting the volume of car sales in PT.Srikandi Diamond Motors using time series data.In the discussion of this research, forecasting using the method of forecasting value Adaptive Spline Threshold Autoregression (ASTAR) produce approximately correct.

A self-organizing Lagrangian particle method for adaptive-resolution advection-diffusion simulations

NASA Astrophysics Data System (ADS)

Reboux, Sylvain; Schrader, Birte; Sbalzarini, Ivo F.

2012-05-01

We present a novel adaptive-resolution particle method for continuous parabolic problems. In this method, particles self-organize in order to adapt to local resolution requirements. This is achieved by pseudo forces that are designed so as to guarantee that the solution is always well sampled and that no holes or clusters develop in the particle distribution. The particle sizes are locally adapted to the length scale of the solution. Differential operators are consistently evaluated on the evolving set of irregularly distributed particles of varying sizes using discretization-corrected operators. The method does not rely on any global transforms or mapping functions. After presenting the method and its error analysis, we demonstrate its capabilities and limitations on a set of two- and three-dimensional benchmark problems. These include advection-diffusion, the Burgers equation, the Buckley-Leverett five-spot problem, and curvature-driven level-set surface refinement.

Nonlinear adaptive inverse control via the unified model neural network

NASA Astrophysics Data System (ADS)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

A Bayesian Hybrid Adaptive Randomisation Design for Clinical Trials with Survival Outcomes.

PubMed

Moatti, M; Chevret, S; Zohar, S; Rosenberger, W F

2016-01-01

Response-adaptive randomisation designs have been proposed to improve the efficiency of phase III randomised clinical trials and improve the outcomes of the clinical trial population. In the setting of failure time outcomes, Zhang and Rosenberger (2007) developed a response-adaptive randomisation approach that targets an optimal allocation, based on a fixed sample size. The aim of this research is to propose a response-adaptive randomisation procedure for survival trials with an interim monitoring plan, based on the following optimal criterion: for fixed variance of the estimated log hazard ratio, what allocation minimizes the expected hazard of failure? We demonstrate the utility of the design by redesigning a clinical trial on multiple myeloma. To handle continuous monitoring of data, we propose a Bayesian response-adaptive randomisation procedure, where the log hazard ratio is the effect measure of interest. Combining the prior with the normal likelihood, the mean posterior estimate of the log hazard ratio allows derivation of the optimal target allocation. We perform a simulation study to assess and compare the performance of this proposed Bayesian hybrid adaptive design to those of fixed, sequential or adaptive - either frequentist or fully Bayesian - designs. Non informative normal priors of the log hazard ratio were used, as well as mixture of enthusiastic and skeptical priors. Stopping rules based on the posterior distribution of the log hazard ratio were computed. The method is then illustrated by redesigning a phase III randomised clinical trial of chemotherapy in patients with multiple myeloma, with mixture of normal priors elicited from experts. As expected, there was a reduction in the proportion of observed deaths in the adaptive vs. non-adaptive designs; this reduction was maximized using a Bayes mixture prior, with no clear-cut improvement by using a fully Bayesian procedure. The use of stopping rules allows a slight decrease in the observed proportion of deaths under the alternate hypothesis compared with the adaptive designs with no stopping rules. Such Bayesian hybrid adaptive survival trials may be promising alternatives to traditional designs, reducing the duration of survival trials, as well as optimizing the ethical concerns for patients enrolled in the trial.

Innovating Method of Existing Mechanical Product Based on TRIZ Theory

NASA Astrophysics Data System (ADS)

Zhao, Cunyou; Shi, Dongyan; Wu, Han

Main way of product development is adaptive design and variant design based on existing product. In this paper, conceptual design frame and its flow model of innovating products is put forward through combining the methods of conceptual design and TRIZ theory. Process system model of innovating design that includes requirement analysis, total function analysis and decomposing, engineering problem analysis, finding solution of engineering problem and primarily design is constructed and this establishes the base for innovating design of existing product.

Strengthening the Social Information-Processing Skills of Children: A Controlled Test of the "Let's Be Friends" Program in China

ERIC Educational Resources Information Center

Wu, Fan; Fraser, Mark W.; Guo, Shenyang; Day, Steven H.; Galinsky, Maeda J.

2016-01-01

Objective: The study had two objectives (a) to adapt for Chinese children an intervention designed to strengthen the social information--processing (SIP) skills of children in the United States, and (b) to pilot test the adapted intervention in China. Methods: Adaptation of the "Making Choices" program involved reviewing Chinese…

Teachers' Pedagogical Competence in Adapting Curricula for Children with Learning Difficulties (LD) in Primary Schools in Ghana

ERIC Educational Resources Information Center

Alhassan, Abdul-Razak Kuyini; Abosi, Chigorom Okechukwu

2017-01-01

Ghana education service (GES) has not achieved much in curriculum adaption to address the needs of children with disability. The aim of this study is to investigate teachers' pedagogical competence (TPC) in curriculum adaptation to include children with LD in primary schools. Mixed-Method Design Strategy involving 387 sampled teachers was used.…

Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

NASA Astrophysics Data System (ADS)

Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

2018-05-01

In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

ERIC Educational Resources Information Center

McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

2016-01-01

Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

Bayesian adaptive phase II screening design for combination trials

PubMed Central

Cai, Chunyan; Yuan, Ying; Johnson, Valen E

2013-01-01

Background Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Methods Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Results Simulation studies show that the proposed design substantially outperforms the conventional multiarm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while allocating substantially more patients to efficacious treatments. Limitations The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. Conclusions The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while providing higher power to identify the best treatment at the end of the trial. PMID:23359875

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Adaptive subdomain modeling: A multi-analysis technique for ocean circulation models

NASA Astrophysics Data System (ADS)

Altuntas, Alper; Baugh, John

2017-07-01

Many coastal and ocean processes of interest operate over large temporal and geographical scales and require a substantial amount of computational resources, particularly when engineering design and failure scenarios are also considered. This study presents an adaptive multi-analysis technique that improves the efficiency of these computations when multiple alternatives are being simulated. The technique, called adaptive subdomain modeling, concurrently analyzes any number of child domains, with each instance corresponding to a unique design or failure scenario, in addition to a full-scale parent domain providing the boundary conditions for its children. To contain the altered hydrodynamics originating from the modifications, the spatial extent of each child domain is adaptively adjusted during runtime depending on the response of the model. The technique is incorporated in ADCIRC++, a re-implementation of the popular ADCIRC ocean circulation model with an updated software architecture designed to facilitate this adaptive behavior and to utilize concurrent executions of multiple domains. The results of our case studies confirm that the method substantially reduces computational effort while maintaining accuracy.

Modular adaptive implant based on smart materials.

PubMed

Bîzdoacă, N; Tarniţă, Daniela; Tarniţă, D N

2008-01-01

Applications of biological methods and systems found in nature to the study and design of engineering systems and modern technology are defined as Bionics. The present paper describes a bionics application of shape memory alloy in construction of orthopedic implant. The main idea of this paper is related to design modular adaptive implants for fractured bones. In order to target the efficiency of medical treatment, the implant has to protect the fractured bone, for the healing period, undertaking much as is possible from the daily usual load of the healthy bones. After a particular stage of healing period is passed, using implant modularity, the load is gradually transferred to bone, assuring in this manner a gradually recover of bone function. The adaptability of this design is related to medical possibility of the physician to made the implant to correspond to patient specifically anatomy. Using a CT realistic numerical bone models, the mechanical simulation of different types of loading of the fractured bones treated with conventional method are presented. The results are commented and conclusions are formulated.

Defining adaptation measures collaboratively: A participatory approach in the Doñana socio-ecological system, Spain.

PubMed

De Stefano, Lucia; Hernández-Mora, Nuria; Iglesias, Ana; Sánchez, Berta

2017-06-15

The uncertainty associated with the definition of strategies for climate change adaptation poses a challenge that cannot be faced by science alone. We present a participatory experience where, instead of having science defining solutions and eliciting stakeholders' feedback, local actors actually drove the process. While principles and methods of the approach are easily adaptable to different local contexts, this paper shows the contribution of participatory dynamics to the design of adaptation measures in the biodiversity-rich socio-ecological region surrounding the Doñana wetlands (Southern Spain). During the process, stakeholders and scientists collaboratively designed a common scenario for the future in which to define and assess a portfolio of potential adaptation measures, and found a safe, informal space for open dialogue and information exchange. Through this dialogue, points of connection among local actors emerged around the need for more integrated, transparent design of adaptation measures; for strengthening local capacity; and for strategies to diversify economic activities in order to increase the resilience of the region. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Adaptive Unstructured Grid Method by Grid Subdivision, Local Remeshing, and Grid Movement

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

1999-01-01

An unstructured grid adaptation technique has been developed and successfully applied to several three dimensional inviscid flow test cases. The approach is based on a combination of grid subdivision, local remeshing, and grid movement. For solution adaptive grids, the surface triangulation is locally refined by grid subdivision, and the tetrahedral grid in the field is partially remeshed at locations of dominant flow features. A grid redistribution strategy is employed for geometric adaptation of volume grids to moving or deforming surfaces. The method is automatic and fast and is designed for modular coupling with different solvers. Several steady state test cases with different inviscid flow features were tested for grid/solution adaptation. In all cases, the dominant flow features, such as shocks and vortices, were accurately and efficiently predicted with the present approach. A new and robust method of moving tetrahedral "viscous" grids is also presented and demonstrated on a three-dimensional example.

From vision to action: roadmapping as a strategic method and tool to implement climate change adaptation - the example of the roadmap 'water sensitive urban design 2020'.

PubMed

Hasse, J U; Weingaertner, D E

2016-01-01

As the central product of the BMBF-KLIMZUG-funded Joint Network and Research Project (JNRP) 'dynaklim - Dynamic adaptation of regional planning and development processes to the effects of climate change in the Emscher-Lippe region (North Rhine Westphalia, Germany)', the Roadmap 2020 'Regional Climate Adaptation' has been developed by the various regional stakeholders and institutions containing specific regional scenarios, strategies and adaptation measures applicable throughout the region. This paper presents the method, elements and main results of this regional roadmap process by using the example of the thematic sub-roadmap 'Water Sensitive Urban Design 2020'. With a focus on the process support tool 'KlimaFLEX', one of the main adaptation measures of the WSUD 2020 roadmap, typical challenges for integrated climate change adaptation like scattered knowledge, knowledge gaps and divided responsibilities but also potential solutions and promising chances for urban development and urban water management are discussed. With the roadmap and the related tool, the relevant stakeholders of the Emscher-Lippe region have jointly developed important prerequisites to integrate their knowledge, to clarify vulnerabilities, adaptation goals, responsibilities and interests, and to foresightedly coordinate measures, resources, priorities and schedules for an efficient joint urban planning, well-grounded decision-making in times of continued uncertainties and step-by-step implementation of adaptation measures from now on.

Multi-fidelity and multi-disciplinary design optimization of supersonic business jets

NASA Astrophysics Data System (ADS)

Choi, Seongim

Supersonic jets have been drawing great attention after the end of service for the Concorde was announced on April of 2003. It is believed, however, that civilian supersonic aircraft may make a viable return in the business jet market. This thesis focuses on the design optimization of feasible supersonic business jet configurations. Preliminary design techniques for mitigation of ground sonic boom are investigated while ensuring that all relevant disciplinary constraints are satisfied (including aerodynamic performance, propulsion, stability & control and structures.) In order to achieve reasonable confidence in the resulting designs, high-fidelity simulations are required, making the entire design process both expensive and complex. In order to minimize the computational cost, surrogate/approximate models are constructed using a hierarchy of different fidelity analysis tools including PASS, A502/Panair and Euler/NS codes. Direct search methods such as Genetic Algorithms (GAs) and a nonlinear SIMPLEX are employed to designs in searches of large and noisy design spaces. A local gradient-based search method can be combined with these global search methods for small modifications of candidate optimum designs. The Mesh Adaptive Direct Search (MADS) method can also be used to explore the design space using a solution-adaptive grid refinement approach. These hybrid approaches, both in search methodology and surrogate model construction, are shown to result in designs with reductions in sonic boom and improved aerodynamic performance.

Adaptive tight frame based medical image reconstruction: a proof-of-concept study for computed tomography

NASA Astrophysics Data System (ADS)

Zhou, Weifeng; Cai, Jian-Feng; Gao, Hao

2013-12-01

A popular approach for medical image reconstruction has been through the sparsity regularization, assuming the targeted image can be well approximated by sparse coefficients under some properly designed system. The wavelet tight frame is such a widely used system due to its capability for sparsely approximating piecewise-smooth functions, such as medical images. However, using a fixed system may not always be optimal for reconstructing a variety of diversified images. Recently, the method based on the adaptive over-complete dictionary that is specific to structures of the targeted images has demonstrated its superiority for image processing. This work is to develop the adaptive wavelet tight frame method image reconstruction. The proposed scheme first constructs the adaptive wavelet tight frame that is task specific, and then reconstructs the image of interest by solving an l1-regularized minimization problem using the constructed adaptive tight frame system. The proof-of-concept study is performed for computed tomography (CT), and the simulation results suggest that the adaptive tight frame method improves the reconstructed CT image quality from the traditional tight frame method.

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

PubMed

Mofid, Omid; Mobayen, Saleh

2018-01-01

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Controller design for a class of nonlinear MIMO coupled system using multiple models and second level adaptation.

PubMed

Pandey, Vinay Kumar; Kar, Indrani; Mahanta, Chitralekha

2017-07-01

In this paper, an adaptive control method using multiple models with second level adaptation is proposed for a class of nonlinear multi-input multi-output (MIMO) coupled systems. Multiple estimation models are used to tune the unknown parameters at the first level. The second level adaptation provides a single parameter vector for the controller. A feedback linearization technique is used to design a state feedback control. The efficacy of the designed controller is validated by conducting real time experiment on a laboratory setup of twin rotor MIMO system (TRMS). The TRMS setup is discussed in detail and the experiments were performed for regulation and tracking problem for pitch and yaw control using different reference signals. An Extended Kalman Filter (EKF) has been used to observe the unavailable states of the TRMS. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Solving delay differential equations in S-ADAPT by method of steps.

PubMed

Bauer, Robert J; Mo, Gary; Krzyzanski, Wojciech

2013-09-01

S-ADAPT is a version of the ADAPT program that contains additional simulation and optimization abilities such as parametric population analysis. S-ADAPT utilizes LSODA to solve ordinary differential equations (ODEs), an algorithm designed for large dimension non-stiff and stiff problems. However, S-ADAPT does not have a solver for delay differential equations (DDEs). Our objective was to implement in S-ADAPT a DDE solver using the methods of steps. The method of steps allows one to solve virtually any DDE system by transforming it to an ODE system. The solver was validated for scalar linear DDEs with one delay and bolus and infusion inputs for which explicit analytic solutions were derived. Solutions of nonlinear DDE problems coded in S-ADAPT were validated by comparing them with ones obtained by the MATLAB DDE solver dde23. The estimation of parameters was tested on the MATLB simulated population pharmacodynamics data. The comparison of S-ADAPT generated solutions for DDE problems with the explicit solutions as well as MATLAB produced solutions which agreed to at least 7 significant digits. The population parameter estimates from using importance sampling expectation-maximization in S-ADAPT agreed with ones used to generate the data. Published by Elsevier Ireland Ltd.

Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2006-01-01

Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

PubMed

Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

2017-07-01

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

Driven Metadynamics: Reconstructing Equilibrium Free Energies from Driven Adaptive-Bias Simulations

PubMed Central

2013-01-01

We present a novel free-energy calculation method that constructively integrates two distinct classes of nonequilibrium sampling techniques, namely, driven (e.g., steered molecular dynamics) and adaptive-bias (e.g., metadynamics) methods. By employing nonequilibrium work relations, we design a biasing protocol with an explicitly time- and history-dependent bias that uses on-the-fly work measurements to gradually flatten the free-energy surface. The asymptotic convergence of the method is discussed, and several relations are derived for free-energy reconstruction and error estimation. Isomerization reaction of an atomistic polyproline peptide model is used to numerically illustrate the superior efficiency and faster convergence of the method compared with its adaptive-bias and driven components in isolation. PMID:23795244

ICASE/LaRC Workshop on Adaptive Grid Methods

NASA Technical Reports Server (NTRS)

South, Jerry C., Jr. (Editor); Thomas, James L. (Editor); Vanrosendale, John (Editor)

1995-01-01

Solution-adaptive grid techniques are essential to the attainment of practical, user friendly, computational fluid dynamics (CFD) applications. In this three-day workshop, experts gathered together to describe state-of-the-art methods in solution-adaptive grid refinement, analysis, and implementation; to assess the current practice; and to discuss future needs and directions for research. This was accomplished through a series of invited and contributed papers. The workshop focused on a set of two-dimensional test cases designed by the organizers to aid in assessing the current state of development of adaptive grid technology. In addition, a panel of experts from universities, industry, and government research laboratories discussed their views of needs and future directions in this field.

Influence of the Size of Cohorts in Adaptive Design for Nonlinear Mixed Effects Models: An Evaluation by Simulation for a Pharmacokinetic and Pharmacodynamic Model for a Biomarker in Oncology

PubMed Central

Lestini, Giulia; Dumont, Cyrielle; Mentré, France

2015-01-01

Purpose In this study we aimed to evaluate adaptive designs (ADs) by clinical trial simulation for a pharmacokinetic-pharmacodynamic model in oncology and to compare them with one-stage designs, i.e. when no adaptation is performed, using wrong prior parameters. Methods We evaluated two one-stage designs, ξ0 and ξ*, optimised for prior and true population parameters, Ψ0 and Ψ*, and several ADs (two-, three- and five-stage). All designs had 50 patients. For ADs, the first cohort design was ξ0. The next cohort design was optimised using prior information updated from the previous cohort. Optimal design was based on the determinant of the Fisher information matrix using PFIM. Design evaluation was performed by clinical trial simulations using data simulated from Ψ*. Results Estimation results of two-stage ADs and ξ* were close and much better than those obtained with ξ0. The balanced two-stage AD performed better than two-stage ADs with different cohort sizes. Three-and five-stage ADs were better than two-stage with small first cohort, but not better than the balanced two-stage design. Conclusions Two-stage ADs are useful when prior parameters are unreliable. In case of small first cohort, more adaptations are needed but these designs are complex to implement. PMID:26123680

Temporally Adaptive Sampling: A Case Study in Rare Species Survey Design with Marbled Salamanders (Ambystoma opacum)

PubMed Central

Charney, Noah D.; Kubel, Jacob E.; Eiseman, Charles S.

2015-01-01

Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds. PMID:25799224

Application of Adaptive Design Methodology in Development of a Long-Acting Glucagon-Like Peptide-1 Analog (Dulaglutide): Statistical Design and Simulations

PubMed Central

Skrivanek, Zachary; Berry, Scott; Berry, Don; Chien, Jenny; Geiger, Mary Jane; Anderson, James H.; Gaydos, Brenda

2012-01-01

Background Dulaglutide (dula, LY2189265), a long-acting glucagon-like peptide-1 analog, is being developed to treat type 2 diabetes mellitus. Methods To foster the development of dula, we designed a two-stage adaptive, dose-finding, inferentially seamless phase 2/3 study. The Bayesian theoretical framework is used to adaptively randomize patients in stage 1 to 7 dula doses and, at the decision point, to either stop for futility or to select up to 2 dula doses for stage 2. After dose selection, patients continue to be randomized to the selected dula doses or comparator arms. Data from patients assigned the selected doses will be pooled across both stages and analyzed with an analysis of covariance model, using baseline hemoglobin A1c and country as covariates. The operating characteristics of the trial were assessed by extensive simulation studies. Results Simulations demonstrated that the adaptive design would identify the correct doses 88% of the time, compared to as low as 6% for a fixed-dose design (the latter value based on frequentist decision rules analogous to the Bayesian decision rules for adaptive design). Conclusions This article discusses the decision rules used to select the dula dose(s); the mathematical details of the adaptive algorithm—including a description of the clinical utility index used to mathematically quantify the desirability of a dose based on safety and efficacy measurements; and a description of the simulation process and results that quantify the operating characteristics of the design. PMID:23294775

Development of Engineering Design Education in the Department of Mechanical Engineering at Kanazawa Technical College

NASA Astrophysics Data System (ADS)

Yamada, Hirofumi; Ten-Nichi, Michio; Mathui, Hirosi; Nakamura, Akizi

This paper introduces a method of the engineering design education for college of technology mechanical engineering students. In order to teach the practical engineering design, the MIL-STD-499A process is adapted and improved upon for a Mechatronics hands-on lesson used as the MOT method. The educational results in five years indicate that knowledge of the engineering management is useful for college students in learning engineering design. Portfolio for lessons and the hypothesis method also have better effects on the understanding of the engineering specialty.

Experiences with an adaptive design for a dose-finding study in patients with osteoarthritis.

PubMed

Miller, Frank; Björnsson, Marcus; Svensson, Ola; Karlsten, Rolf

2014-03-01

Dose-finding studies in non-oncology areas are usually conducted in Phase II of the development process of a new potential medicine and it is key to choose a good design for such a study, as the results will decide if and how to proceed to Phase III. The present article has focus on the design of a dose-finding study for pain in osteoarthritis patients treated with the TRPV1 antagonist AZD1386. We describe different design alternatives in the planning of this study, the reasoning for choosing the adaptive design and experiences with conduct and interim analysis. Three alternatives were proposed: one single dose-finding study with parallel design, a programme with a smaller Phase IIa study followed by a Phase IIb dose-finding study, and an adaptive dose-finding study. We describe these alternatives in detail and explain why the adaptive design was chosen for the study. We give insights in design aspects of the adaptive study, which need to be pre-planned, like interim decision criteria, statistical analysis method and setup of a Data Monitoring Committee. Based on the interim analysis it was recommended to stop the study for futility since AZD1386 showed no significant pain decrease based on the primary variable. We discuss results and experiences from the conduct of the study with the novel design approach. Huge cost savings have been done compared to if the option with one dose-finding design for Phase II had been chosen. However, we point out several challenges with this approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Method Engineering: A Service-Oriented Approach

NASA Astrophysics Data System (ADS)

Cauvet, Corine

In the past, a large variety of methods have been published ranging from very generic frameworks to methods for specific information systems. Method Engineering has emerged as a research discipline for designing, constructing and adapting methods for Information Systems development. Several approaches have been proposed as paradigms in method engineering. The meta modeling approach provides means for building methods by instantiation, the component-based approach aims at supporting the development of methods by using modularization constructs such as method fragments, method chunks and method components. This chapter presents an approach (SO2M) for method engineering based on the service paradigm. We consider services as autonomous computational entities that are self-describing, self-configuring and self-adapting. They can be described, published, discovered and dynamically composed for processing a consumer's demand (a developer's requirement). The method service concept is proposed to capture a development process fragment for achieving a goal. Goal orientation in service specification and the principle of service dynamic composition support method construction and method adaptation to different development contexts.

Adaptive control method for core power control in TRIGA Mark II reactor

NASA Astrophysics Data System (ADS)

Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

2018-01-01

The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

Culturally Adaptive Walking Intervention for Korean-Chinese Female Migrant Workers.

PubMed

Cho, Sunghye; Lee, Hyeonkyeong; Kim, Jung Hee; Lee, Meenhye; Lee, Young-Me

2017-05-01

Although the literature has commonly cited that development of culturally adaptive interventions is key to improving the health outcomes of culturally and linguistically diverse populations, there have been limited culturally adaptive walking interventions specific to Korean-Chinese (KC) migrants. The objective of this study is to describe the process in development of culturally adaptive walking interventions for KC female migrant workers, using the intervention mapping (IM) method. The culturally adaptive walking intervention was developed using the IM method, which is a stepwise theory and evidence-based approach for planning interventions. The IM method process has six steps, including needs assessment, formulation of change objectives, selection of theory-based methods and practical strategies, development of an intervention program, development of an adoption and implementation plan, and development of an evaluation design. The determinants of walking behavior, including knowledge, self-efficacy, social support, and acculturation, were identified through an extensive literature review, community leader interviews, and a survey of female KC migrant workers. Appropriate intervention methods and strategies were identified based on relevant theories. Acculturation was a determinant of exercise behavior, and various methods to improve cultural adaptation were identified in the context of the lifestyles and working environments of the target population. The IM method provided a foundation for creating a health intervention for KC female migrant workers. This method could easily be useful for health care providers working with other groups.

An adaptive response surface method for crashworthiness optimization

NASA Astrophysics Data System (ADS)

Shi, Lei; Yang, Ren-Jye; Zhu, Ping

2013-11-01

Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.

A Tutorial on Adaptive Design Optimization

PubMed Central

Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

2013-01-01

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study

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

Ahmad, Israr, E-mail: iak-2000plus@yahoo.com; Saaban, Azizan Bin, E-mail: azizan.s@uum.edu.my; Ibrahim, Adyda Binti, E-mail: adyda@uum.edu.my

This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.

Augmented Adaptive Control of a Wind Turbine in the Presence of Structural Modes

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.; Wright, Alan D.

2010-01-01

Wind turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, potentially causing component fatigue and failure. Two key technology drivers for turbine manufacturers are increasing turbine up time and reducing maintenance costs. Since the trend in wind turbine design is towards larger, more flexible turbines with lower frequency structural modes, manufacturers will want to develop methods to operate in the presence of these modes. Accurate models of the dynamic characteristics of new wind turbines are often not available due to the complexity and expense of the modeling task, making wind turbines ideally suited to adaptive control. In this paper, we develop theory for adaptive control with rejection of disturbances in the presence of modes that inhibit the controller. We use this method to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the interference of certain structural modes in feedback. The control objective is accomplished by collectively pitching the turbine blades. The adaptive pitch controller for Region 3 is compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller.

Application of Adaptive DP-optimality to Design a Pilot Study for a Clotting Time Test for Enoxaparin.

PubMed

Gulati, Abhishek; Faed, James M; Isbister, Geoffrey K; Duffull, Stephen B

2015-10-01

Dosing of enoxaparin, like other anticoagulants, may result in bleeding following excessive doses and clot formation if the dose is too low. We recently showed that a factor Xa based clotting time test could potentially assess the effect of enoxaparin on the clotting system. However, the test did not perform well in subsequent individuals and effectiveness of an exogenous phospholipid, Actin FS, in reducing the variability in the clotting time was assessed. The aim of this work was to conduct an adaptive pilot study to determine the range of concentrations of Xa and Actin FS to take forward into a proof-of-concept study. A nonlinear parametric function was developed to describe the response surface over the factors of interest. An adaptive method was used to estimate the parameters using a D-optimal design criterion. In order to provide a reasonable probability of observing a success of the clotting time test, a P-optimal design criterion was incorporated using a loss function to describe the hybrid DP-optimality. The use of adaptive DP-optimality method resulted in an efficient estimation of model parameters using data from only 6 healthy volunteers. The use of response surface modelling identified a range of sets of Xa and Actin FS concentrations, any of which could be used for the proof-of-concept study. This study shows that parsimonious adaptive DP-optimal designs may provide both precise parameter estimates for response surface modelling as well as clinical confidence in the potential benefits of the study.

Method study on fuzzy-PID adaptive control of electric-hydraulic hitch system

NASA Astrophysics Data System (ADS)

Li, Mingsheng; Wang, Liubu; Liu, Jian; Ye, Jin

2017-03-01

In this paper, fuzzy-PID adaptive control method is applied to the control of tractor electric-hydraulic hitch system. According to the characteristics of the system, a fuzzy-PID adaptive controller is designed and the electric-hydraulic hitch system model is established. Traction control and position control performance simulation are carried out with the common PID control method. A field test rig was set up to test the electric-hydraulic hitch system. The test results showed that, after the fuzzy-PID adaptive control is adopted, when the tillage depth steps from 0.1m to 0.3m, the system transition process time is 4s, without overshoot, and when the tractive force steps from 3000N to 7000N, the system transition process time is 5s, the system overshoot is 25%.

A modified method for COD determination of solid waste, using a commercial COD kit and an adapted disposable weighing support.

PubMed

André, L; Pauss, A; Ribeiro, T

2017-03-01

The chemical oxygen demand (COD) is an essential parameter in waste management, particularly when monitoring wet anaerobic digestion processes. An adapted method to determine COD was developed for solid waste (total solids >15%). This method used commercial COD tubes and did not require sample dilution. A homemade plastic weighing support was used to transfer the solid sample into COD tubes. Potassium hydrogen phthalate and glucose used as standards showed an excellent repeatability. A small underestimation of the theoretical COD value (standard values around 5% lower than theoretical values) was also observed, mainly due to the intrinsic COD of the weighing support and to measurement uncertainties. The adapted COD method was tested using various solid wastes in the range of 1-8 mg COD , determining the COD of dried and ground cellulose, cattle manure, straw and a mixed-substrate sample. This new adapted method could be used to monitor and design dry anaerobic digestion processes.

Virtual reality based adaptive dose assessment method for arbitrary geometries in nuclear facility decommissioning.

PubMed

Liu, Yong-Kuo; Chao, Nan; Xia, Hong; Peng, Min-Jun; Ayodeji, Abiodun

2018-05-17

This paper presents an improved and efficient virtual reality-based adaptive dose assessment method (VRBAM) applicable to the cutting and dismantling tasks in nuclear facility decommissioning. The method combines the modeling strength of virtual reality with the flexibility of adaptive technology. The initial geometry is designed with the three-dimensional computer-aided design tools, and a hybrid model composed of cuboids and a point-cloud is generated automatically according to the virtual model of the object. In order to improve the efficiency of dose calculation while retaining accuracy, the hybrid model is converted to a weighted point-cloud model, and the point kernels are generated by adaptively simplifying the weighted point-cloud model according to the detector position, an approach that is suitable for arbitrary geometries. The dose rates are calculated with the Point-Kernel method. To account for radiation scattering effects, buildup factors are calculated with the Geometric-Progression formula in the fitting function. The geometric modeling capability of VRBAM was verified by simulating basic geometries, which included a convex surface, a concave surface, a flat surface and their combination. The simulation results show that the VRBAM is more flexible and superior to other approaches in modeling complex geometries. In this paper, the computation time and dose rate results obtained from the proposed method were also compared with those obtained using the MCNP code and an earlier virtual reality-based method (VRBM) developed by the same authors. © 2018 IOP Publishing Ltd.

Course Design and Student Learning.

ERIC Educational Resources Information Center

Billing, David, Ed.

Papers presented at the Society for Research into Higher Education's conference on course design and student learning dealt with the following overall topics: the needs of special groups of students; student involvement; study skills and learning methods; course design; and employment, adaptation, and socialization. Among the papers presented were…

Design of multi-view stereoscopic HD video transmission system based on MPEG-21 digital item adaptation

NASA Astrophysics Data System (ADS)

Lee, Seokhee; Lee, Kiyoung; Kim, Man Bae; Kim, JongWon

2005-11-01

In this paper, we propose a design of multi-view stereoscopic HD video transmission system based on MPEG-21 Digital Item Adaptation (DIA). It focuses on the compatibility and scalability to meet various user preferences and terminal capabilities. There exist a large variety of multi-view 3D HD video types according to the methods for acquisition, display, and processing. By following the MPEG-21 DIA framework, the multi-view stereoscopic HD video is adapted according to user feedback. A user can be served multi-view stereoscopic video which corresponds with his or her preferences and terminal capabilities. In our preliminary prototype, we verify that the proposed design can support two deferent types of display device (stereoscopic and auto-stereoscopic) and switching viewpoints between two available viewpoints.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

PubMed

Zhang, Jin-Xi; Yang, Guang-Hong

2018-05-01

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

A Phase I/II adaptive design for heterogeneous groups with application to a stereotactic body radiation therapy trial.

PubMed

Wages, Nolan A; Read, Paul W; Petroni, Gina R

2015-01-01

Dose-finding studies that aim to evaluate the safety of single agents are becoming less common, and advances in clinical research have complicated the paradigm of dose finding in oncology. A class of more complex problems, such as targeted agents, combination therapies and stratification of patients by clinical or genetic characteristics, has created the need to adapt early-phase trial design to the specific type of drug being investigated and the corresponding endpoints. In this article, we describe the implementation of an adaptive design based on a continual reassessment method for heterogeneous groups, modified to coincide with the objectives of a Phase I/II trial of stereotactic body radiation therapy in patients with painful osseous metastatic disease. Operating characteristics of the Institutional Review Board approved design are demonstrated under various possible true scenarios via simulation studies. Copyright © 2015 John Wiley & Sons, Ltd.

Database Design Learning: A Project-Based Approach Organized through a Course Management System

ERIC Educational Resources Information Center

Dominguez, Cesar; Jaime, Arturo

2010-01-01

This paper describes an active method for database design learning through practical tasks development by student teams in a face-to-face course. This method integrates project-based learning, and project management techniques and tools. Some scaffolding is provided at the beginning that forms a skeleton that adapts to a great variety of…

A “SMART” Design for Building Individualized Treatment Sequences

PubMed Central

Lei, H.; Nahum-Shani, I.; Lynch, K.; Oslin, D.; Murphy, S.A.

2013-01-01

Interventions often involve a sequence of decisions. For example, clinicians frequently adapt the intervention to an individual’s outcomes. Altering the intensity and type of intervention over time is crucial for many reasons, such as to obtain improvement if the individual is not responding or to reduce costs and burden when intensive treatment is no longer necessary. Adaptive interventions utilize individual variables (severity, preferences) to adapt the intervention and then dynamically utilize individual outcomes (response to treatment, adherence) to readapt the intervention. The Sequential Multiple Assignment Randomized Trial (SMART)provides high-quality data that can be used to construct adaptive interventions. We review the SMART and highlight its advantages in constructing and revising adaptive interventions as compared to alternative experimental designs. Selected examples of SMART studies are described and compared. A data analysis method is provided and illustrated using data from the Extending Treatment Effectiveness of Naltrexone SMART study. PMID:22224838

Experimental aeroelastic control using adaptive wing model concepts

NASA Astrophysics Data System (ADS)

Costa, Antonio P.; Moniz, Paulo A.; Suleman, Afzal

2001-06-01

The focus of this study is to evaluate the aeroelastic performance and control of adaptive wings. Ailerons and flaps have been designed and implemented into 3D wings for comparison with adaptive structures and active aerodynamic surface control methods. The adaptive structures concept, the experimental setup and the control design are presented. The wind-tunnel tests of the wing models are presented for the open- and closed-loop systems. The wind tunnel testing has allowed for quantifying the effectiveness of the piezoelectric vibration control of the wings, and also provided performance data for comparison with conventional aerodynamic control surfaces. The results indicate that a wing utilizing skins as active structural elements with embedded piezoelectric actuators can be effectively used to improve the aeroelastic response of aeronautical components. It was also observed that the control authority of adaptive wings is much greater than wings using conventional aerodynamic control surfaces.

On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\\infty}$ Control.

PubMed

Wang, Ding; Mu, Chaoxu; Liu, Derong; Ma, Hongwen

2018-04-01

In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

Implementing resilience engineering for healthcare quality improvement using the CARE model: a feasibility study protocol.

PubMed

Anderson, J E; Ross, A J; Back, J; Duncan, M; Snell, P; Walsh, K; Jaye, P

2016-01-01

Resilience engineering (RE) is an emerging perspective on safety in complex adaptive systems that emphasises how outcomes emerge from the complexity of the clinical environment. Complexity creates the need for flexible adaptation to achieve outcomes. RE focuses on understanding the nature of adaptations, learning from success and increasing adaptive capacity. Although the philosophy is clear, progress in applying the ideas to quality improvement has been slow. The aim of this study is to test the feasibility of translating RE concepts into practical methods to improve quality by designing, implementing and evaluating interventions based on RE theory. The CARE model operationalises the key concepts and their relationships to guide the empirical investigation. The settings are the Emergency Department and the Older Person's Unit in a large London teaching hospital. Phases 1 and 2 of our work, leading to the development of interventions to improve the quality of care, are described in this paper. Ethical approval has been granted for these phases. Phase 1 will use ethnographic methods, including observation of work practices and interviews with staff, to understand adaptations and outcomes. The findings will be used to collaboratively design, with clinical staff in interactive design workshops, interventions to improve the quality of care. The evaluation phase will be designed and submitted for ethical approval when the outcomes of phases 1 and 2 are known. Study outcomes will be knowledge about the feasibility of applying RE to improve quality, the development of RE theory and a validated model of resilience in clinical work which can be used to guide other applications. Tools, methods and practical guidance for practitioners will also be produced, as well as specific knowledge of the potential effectiveness of the implemented interventions in emergency and older people's care. Further studies to test the application of RE at a larger scale will be required, including studies of other healthcare settings, organisational contexts and different interventions.

Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty

NASA Astrophysics Data System (ADS)

Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design, thus alleviating the risk of mis-adaptation, namely the design of a solution fully adapted to a scenario that is different from the one that will actually realize.

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter.

PubMed

Fei, Juntao; Zhu, Yunkai

2017-01-01

In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP) by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance.

Genetic potential of black bean genotypes with predictable behaviors in multienvironment trials.

PubMed

Torga, P P; Melo, P G S; Pereira, H S; Faria, L C; Melo, L C

2016-10-24

The aim of this study was to evaluate the phenotypic stability and specific and broad adaptability of common black bean genotypes for the Central and Center-South regions of Brazil by using the Annicchiarico and AMMI (weighted average of absolute scores: WAAS, and weighted average of absolute scores and productivity: WAASP) methodologies. We carried out 69 trials, with 43 and 26 trials in the Central and Center-South regions, respectively. Thirteen genotypes were evaluated in a randomized block design with three replications, during the rainy, dry, and winter seasons in 2 years. To obtain estimates of specific adaptation, we analyzed the parameters for each method obtained in the two geographic regions separately. To estimate broad adaptation, we used the average of the parameters obtained from each region. The lines identified with high specific adaptation in each region were not the same based on the Annicchiarico and AMMI (WAAS) methodologies. It was not possible to identify the same genotypes with specific or broad stability by using these methods. By contrast, the Annicchiarico and AMMI (WAASP) methods presented very similar estimates of broad and specific adaptation. Based on these methods, the lines with more specific adaptation were CNFP 8000 and CNFP 7994, in the Central and Center-South regions, respectively, of which the CNFP 8000 line was more widely adapted.

SVAS3: Strain Vector Aided Sensorization of Soft Structures.

PubMed

Culha, Utku; Nurzaman, Surya G; Clemens, Frank; Iida, Fumiya

2014-07-17

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Mutual information based feature selection for medical image retrieval

NASA Astrophysics Data System (ADS)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Robust Design of Sheet Metal Forming Process Based on Kriging Metamodel

NASA Astrophysics Data System (ADS)

Xie, Yanmin

2011-08-01

Nowadays, sheet metal forming processes design is not a trivial task due to the complex issues to be taken into account (conflicting design goals, complex shapes forming and so on). Optimization methods have also been widely applied in sheet metal forming. Therefore, proper design methods to reduce time and costs have to be developed mostly based on computer aided procedures. At the same time, the existence of variations during manufacturing processes significantly may influence final product quality, rendering non-robust optimal solutions. In this paper, a small size of design of experiments is conducted to investigate how a stochastic behavior of noise factors affects drawing quality. The finite element software (LS_DYNA) is used to simulate the complex sheet metal stamping processes. The Kriging metamodel is adopted to map the relation between input process parameters and part quality. Robust design models for sheet metal forming process integrate adaptive importance sampling with Kriging model, in order to minimize impact of the variations and achieve reliable process parameters. In the adaptive sample, an improved criterion is used to provide direction in which additional training samples can be added to better the Kriging model. Nonlinear functions as test functions and a square stamping example (NUMISHEET'93) are employed to verify the proposed method. Final results indicate application feasibility of the aforesaid method proposed for multi-response robust design.

Indirect learning control for nonlinear dynamical systems

NASA Technical Reports Server (NTRS)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Bridging Scientific Reasoning and Conceptual Change through Adaptive Web-Based Learning

ERIC Educational Resources Information Center

She, Hsiao-Ching; Liao, Ya-Wen

2010-01-01

This study reports an adaptive digital learning project, Scientific Concept Construction and Reconstruction (SCCR), and examines its effects on 108 8th grade students' scientific reasoning and conceptual change through mixed methods. A one-group pre-, post-, and retention quasi-experimental design was used in the study. All students received tests…

Understanding the Art and Science of Implementation in the SAAF Efficacy Trial

ERIC Educational Resources Information Center

Berkel, Cady; Murry, Velma McBride; Roulston, Kathryn J.; Brody, Gene H.

2013-01-01

Purpose: The purpose of this paper is to demonstrate the importance of considering both fidelity and adaptation in assessing the implementation of evidence-based programs. Design/methodology/approach: The current study employs a multi-method strategy to understand two dimensions of implementation (fidelity and adaptation) in the Strong African…

Adaptation of aeronautical engines to high altitude flying

NASA Technical Reports Server (NTRS)

Kutzbach, K

1923-01-01

Issues and techniques relative to the adaptation of aircraft engines to high altitude flight are discussed. Covered here are the limits of engine output, modifications and characteristics of high altitude engines, the influence of air density on the proportions of fuel mixtures, methods of varying the proportions of fuel mixtures, the automatic prevention of fuel waste, and the design and application of air pressure regulators to high altitude flying. Summary: 1. Limits of engine output. 2. High altitude engines. 3. Influence of air density on proportions of mixture. 4. Methods of varying proportions of mixture. 5. Automatic prevention of fuel waste. 6. Design and application of air pressure regulators to high altitude flying.

Detection of circuit-board components with an adaptive multiclass correlation filter

NASA Astrophysics Data System (ADS)

Diaz-Ramirez, Victor H.; Kober, Vitaly

2008-08-01

A new method for reliable detection of circuit-board components is proposed. The method is based on an adaptive multiclass composite correlation filter. The filter is designed with the help of an iterative algorithm using complex synthetic discriminant functions. The impulse response of the filter contains information needed to localize and classify geometrically distorted circuit-board components belonging to different classes. Computer simulation results obtained with the proposed method are provided and compared with those of known multiclass correlation based techniques in terms of performance criteria for recognition and classification of objects.

Adaptive control for eye-gaze input system

NASA Astrophysics Data System (ADS)

Zhao, Qijie; Tu, Dawei; Yin, Hairong

2004-01-01

The characteristics of the vision-based human-computer interaction system have been analyzed, and the practical application and its limited factors at present time have also been mentioned. The information process methods have been put forward. In order to make the communication flexible and spontaneous, the algorithms to adaptive control of user"s head movement has been designed, and the events-based methods and object-oriented computer language is used to develop the system software, by experiment testing, we found that under given condition, these methods and algorithms can meet the need of the HCI.

Multidisciplinary optimization of a controlled space structure using 150 design variables

NASA Technical Reports Server (NTRS)

James, Benjamin B.

1992-01-01

A general optimization-based method for the design of large space platforms through integration of the disciplines of structural dynamics and control is presented. The method uses the global sensitivity equations approach and is especially appropriate for preliminary design problems in which the structural and control analyses are tightly coupled. The method is capable of coordinating general purpose structural analysis, multivariable control, and optimization codes, and thus, can be adapted to a variety of controls-structures integrated design projects. The method is used to minimize the total weight of a space platform while maintaining a specified vibration decay rate after slewing maneuvers.

QUEST+: A general multidimensional Bayesian adaptive psychometric method.

PubMed

Watson, Andrew B

2017-03-01

QUEST+ is a Bayesian adaptive psychometric testing method that allows an arbitrary number of stimulus dimensions, psychometric function parameters, and trial outcomes. It is a generalization and extension of the original QUEST procedure and incorporates many subsequent developments in the area of parametric adaptive testing. With a single procedure, it is possible to implement a wide variety of experimental designs, including conventional threshold measurement; measurement of psychometric function parameters, such as slope and lapse; estimation of the contrast sensitivity function; measurement of increment threshold functions; measurement of noise-masking functions; Thurstone scale estimation using pair comparisons; and categorical ratings on linear and circular stimulus dimensions. QUEST+ provides a general method to accelerate data collection in many areas of cognitive and perceptual science.

Design Fixation and Cooperative Learning in Elementary Engineering Design Project: A Case Study

ERIC Educational Resources Information Center

Luo, Yi

2015-01-01

This paper presents a case study examining 3rd, 4th and 5th graders' design fixation and cooperative learning in an engineering design project. A mixed methods instrument, the Cooperative Learning Observation Protocol (CLOP), was adapted to record frequency and class observation on cooperative learning engagement through detailed field notes.…

Stress adapted embroidered meshes with a graded pattern design for abdominal wall hernia repair

NASA Astrophysics Data System (ADS)

Hahn, J.; Bittrich, L.; Breier, A.; Spickenheuer, A.

2017-10-01

Abdominal wall hernias are one of the most relevant injuries of the digestive system with 25 million patients in 2013. Surgery is recommended primarily using allogenic non-absorbable wrap-knitted meshes. These meshes have in common that their stress-strain behaviour is not adapted to the anisotropic behaviour of native abdominal wall tissue. The ideal mesh should possess an adequate mechanical behaviour and a suitable porosity at the same time. An alternative fabrication method to wrap-knitting is the embroidery technology with a high flexibility in pattern design and adaption of mechanical properties. In this study, a pattern generator was created for pattern designs consisting of a base and a reinforcement pattern. The embroidered mesh structures demonstrated different structural and mechanical characteristics. Additionally, the investigation of the mechanical properties exhibited an anisotropic mechanical behaviour for the embroidered meshes. As a result, the investigated pattern generator and the embroidery technology allow the production of stress adapted mesh structures that are a promising approach for hernia reconstruction.

Design and analysis of adaptive Super-Twisting sliding mode control for a microgyroscope.

PubMed

Feng, Zhilin; Fei, Juntao

2018-01-01

This paper proposes a novel adaptive Super-Twisting sliding mode control for a microgyroscope under unknown model uncertainties and external disturbances. In order to improve the convergence rate of reaching the sliding surface and the accuracy of regulating and trajectory tracking, a high order Super-Twisting sliding mode control strategy is employed, which not only can combine the advantages of the traditional sliding mode control with the Super-Twisting sliding mode control, but also guarantee that the designed control system can reach the sliding surface and equilibrium point in a shorter finite time from any initial state and avoid chattering problems. In consideration of unknown parameters of micro gyroscope system, an adaptive algorithm based on Lyapunov stability theory is designed to estimate the unknown parameters and angular velocity of microgyroscope. Finally, the effectiveness of the proposed scheme is demonstrated by simulation results. The comparative study between adaptive Super-Twisting sliding mode control and conventional sliding mode control demonstrate the superiority of the proposed method.

The DIAN-TU Next Generation Alzheimer’s prevention trial: adaptive design and disease progression model

PubMed Central

Bateman, Randall J.; Benzinger, Tammie L.; Berry, Scott; Clifford, David B.; Duggan, Cynthia; Fagan, Anne M.; Fanning, Kathleen; Farlow, Martin R.; Hassenstab, Jason; McDade, Eric M.; Mills, Susan; Paumier, Katrina; Quintana, Melanie; Salloway, Stephen P.; Santacruz, Anna; Schneider, Lon S.; Wang, Guoqiao; Xiong, Chengjie

2016-01-01

INTRODUCTION The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer’s disease in autosomal dominant Alzheimer’s disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation Prevention Trial (NexGen). METHODS In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the NIH, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen trial. RESULTS Our expanded trials toolbox consists of a Disease Progression Model for ADAD, primary endpoint DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD. PMID:27583651

Adaptive Neural Control for a Class of Pure-Feedback Nonlinear Systems via Dynamic Surface Technique.

PubMed

Liu, Zongcheng; Dong, Xinmin; Xue, Jianping; Li, Hongbo; Chen, Yong

2016-09-01

This brief addresses the adaptive control problem for a class of pure-feedback systems with nonaffine functions possibly being nondifferentiable. Without using the mean value theorem, the difficulty of the control design for pure-feedback systems is overcome by modeling the nonaffine functions appropriately. With the help of neural network approximators, an adaptive neural controller is developed by combining the dynamic surface control (DSC) and minimal learning parameter (MLP) techniques. The key features of our approach are that, first, the restrictive assumptions on the partial derivative of nonaffine functions are removed, second, the DSC technique is used to avoid "the explosion of complexity" in the backstepping design, and the number of adaptive parameters is reduced significantly using the MLP technique, third, smooth robust compensators are employed to circumvent the influences of approximation errors and disturbances. Furthermore, it is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded. Finally, the simulation results are provided to demonstrate the effectiveness of the designed method.

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Reconfigurable Model Execution in the OpenMDAO Framework

NASA Technical Reports Server (NTRS)

Hwang, John T.

2017-01-01

NASA's OpenMDAO framework facilitates constructing complex models and computing their derivatives for multidisciplinary design optimization. Decomposing a model into components that follow a prescribed interface enables OpenMDAO to assemble multidisciplinary derivatives from the component derivatives using what amounts to the adjoint method, direct method, chain rule, global sensitivity equations, or any combination thereof, using the MAUD architecture. OpenMDAO also handles the distribution of processors among the disciplines by hierarchically grouping the components, and it automates the data transfer between components that are on different processors. These features have made OpenMDAO useful for applications in aircraft design, satellite design, wind turbine design, and aircraft engine design, among others. This paper presents new algorithms for OpenMDAO that enable reconfigurable model execution. This concept refers to dynamically changing, during execution, one or more of: the variable sizes, solution algorithm, parallel load balancing, or set of variables-i.e., adding and removing components, perhaps to switch to a higher-fidelity sub-model. Any component can reconfigure at any point, even when running in parallel with other components, and the reconfiguration algorithm presented here performs the synchronized updates to all other components that are affected. A reconfigurable software framework for multidisciplinary design optimization enables new adaptive solvers, adaptive parallelization, and new applications such as gradient-based optimization with overset flow solvers and adaptive mesh refinement. Benchmarking results demonstrate the time savings for reconfiguration compared to setting up the model again from scratch, which can be significant in large-scale problems. Additionally, the new reconfigurability feature is applied to a mission profile optimization problem for commercial aircraft where both the parametrization of the mission profile and the time discretization are adaptively refined, resulting in computational savings of roughly 10% and the elimination of oscillations in the optimized altitude profile.

Understanding the leaky engineering pipeline: Motivation and job adaptability of female engineers

NASA Astrophysics Data System (ADS)

Saraswathiamma, Manjusha Thekkedathu

This dissertation is a mixed-method study conducted using qualitative grounded theory and quantitative survey and correlation approaches. This study aims to explore the motivation and adaptability of females in the engineering profession and to develop a theoretical framework for both motivation and adaptability issues. As a result, this study endeavors to design solutions for the low enrollment and attenuation of female engineers in the engineering profession, often referred to as the "leaky female engineering pipeline." Profiles of 123 female engineers were studied for the qualitative approach, and 98 completed survey responses were analyzed for the quantitative approach. The qualitative, grounded-theory approach applied the constant comparison method; open, axial, and selective coding was used to classify the information in categories, sub-categories, and themes for both motivation and adaptability. The emergent themes for decisions motivating female enrollment include cognitive, emotional, and environmental factors. The themes identified for adaptability include the seven job adaptability factors: job satisfaction, risk- taking attitude, career/skill development, family, gender stereotyping, interpersonal skills, and personal benefit, as well as the self-perceived job adaptability factor. Illeris' Three-dimensional Learning Theory was modified as a model for decisions motivating female enrollment. This study suggests a firsthand conceptual parallelism of McClusky's Theory of Margin for the adaptability of female engineers in the profession. Also, this study attempted to design a survey instrument to measure job adaptability of female engineers. The study identifies two factors that are significantly related to job adaptability: interpersonal skills (< p = 0.01) and family (< p = 0.05); gender stereotyping and personal benefit are other factors that are also significantly (< p = 0.1) related.

Adjoint-Based Mesh Adaptation for the Sonic Boom Signature Loudness

NASA Technical Reports Server (NTRS)

Rallabhandi, Sriram K.; Park, Michael A.

2017-01-01

The mesh adaptation functionality of FUN3D is utilized to obtain a mesh optimized to calculate sonic boom ground signature loudness. During this process, the coupling between the discrete-adjoints of the computational fluid dynamics tool FUN3D and the atmospheric propagation tool sBOOM is exploited to form the error estimate. This new mesh adaptation methodology will allow generation of suitable meshes adapted to reduce the estimated errors in the ground loudness, which is an optimization metric employed in supersonic aircraft design. This new output-based adaptation could allow new insights into meshing for sonic boom analysis and design, and complements existing output-based adaptation techniques such as adaptation to reduce estimated errors in off-body pressure functional. This effort could also have implications for other coupled multidisciplinary adjoint capabilities (e.g., aeroelasticity) as well as inclusion of propagation specific parameters such as prevailing winds or non-standard atmospheric conditions. Results are discussed in the context of existing methods and appropriate conclusions are drawn as to the efficacy and efficiency of the developed capability.

Evolving a Method to Capture Science Stakeholder Inputs to Optimize Instrument, Payload, and Program Design

NASA Astrophysics Data System (ADS)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.; Bailin, S.

2012-03-01

We are developing Frontier, a highly adaptable, stably reconfigurable, web-accessible intelligent decision engine capable of optimizing design as well as the simulating operation of complex systems in response to evolving needs and environment.

Local Laser Strengthening of Steel Sheets for Load Adapted Component Design in Car Body Structures

NASA Astrophysics Data System (ADS)

Jahn, Axel; Heitmanek, Marco; Standfuss, Jens; Brenner, Berndt; Wunderlich, Gerd; Donat, Bernd

The current trend in car body construction concerning light weight design and car safety improvement increasingly requires an adaption of the local material properties on the component load. Martensitic hardenable steels, which are typically used in car body components, show a significant hardening effect, for instance in laser welded seams. This effect can be purposefully used as a local strengthening method. For several steel grades the local strengthening, resulting from a laser remelting process was investigated. The strength in the treated zone was determined at crash relevant strain rates. A load adapted design of complex reinforcement structures was developed for compression and bending loaded tube samples, using numerical simulation of the deformation behavior. Especially for bending loaded parts, the crash energy absorption can be increased significantly by local laser strengthening.

An adaptive sampling method for variable-fidelity surrogate models using improved hierarchical kriging

NASA Astrophysics Data System (ADS)

Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli

2018-01-01

Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.

A review of parametric approaches specific to aerodynamic design process

NASA Astrophysics Data System (ADS)

Zhang, Tian-tian; Wang, Zhen-guo; Huang, Wei; Yan, Li

2018-04-01

Parametric modeling of aircrafts plays a crucial role in the aerodynamic design process. Effective parametric approaches have large design space with a few variables. Parametric methods that commonly used nowadays are summarized in this paper, and their principles have been introduced briefly. Two-dimensional parametric methods include B-Spline method, Class/Shape function transformation method, Parametric Section method, Hicks-Henne method and Singular Value Decomposition method, and all of them have wide application in the design of the airfoil. This survey made a comparison among them to find out their abilities in the design of the airfoil, and the results show that the Singular Value Decomposition method has the best parametric accuracy. The development of three-dimensional parametric methods is limited, and the most popular one is the Free-form deformation method. Those methods extended from two-dimensional parametric methods have promising prospect in aircraft modeling. Since different parametric methods differ in their characteristics, real design process needs flexible choice among them to adapt to subsequent optimization procedure.

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

NASA Technical Reports Server (NTRS)

Hartley, Tom T. (Editor)

1987-01-01

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

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.

An Adaptive Instability Suppression Controls Method for Aircraft Gas Turbine Engine Combustors

NASA Technical Reports Server (NTRS)

Kopasakis, George; DeLaat, John C.; Chang, Clarence T.

2008-01-01

An adaptive controls method for instability suppression in gas turbine engine combustors has been developed and successfully tested with a realistic aircraft engine combustor rig. This testing was part of a program that demonstrated, for the first time, successful active combustor instability control in an aircraft gas turbine engine-like environment. The controls method is called Adaptive Sliding Phasor Averaged Control. Testing of the control method has been conducted in an experimental rig with different configurations designed to simulate combustors with instabilities of about 530 and 315 Hz. Results demonstrate the effectiveness of this method in suppressing combustor instabilities. In addition, a dramatic improvement in suppression of the instability was achieved by focusing control on the second harmonic of the instability. This is believed to be due to a phenomena discovered and reported earlier, the so called Intra-Harmonic Coupling. These results may have implications for future research in combustor instability control.

An improved adaptive control for repetitive motion of robots

NASA Technical Reports Server (NTRS)

Pourboghrat, F.

1989-01-01

An adaptive control algorithm is proposed for a class of nonlinear systems, such as robotic manipulators, which is capable of improving its performance in repetitive motions. When the task is repeated, the error between the desired trajectory and that of the system is guaranteed to decrease. The design is based on the combination of a direct adaptive control and a learning process. This method does not require any knowledge of the dynamic parameters of the system.

Developing the evidence base for mainstreaming adaptation of stormwater systems to climate change.

PubMed

Gersonius, B; Nasruddin, F; Ashley, R; Jeuken, A; Pathirana, A; Zevenbergen, C

2012-12-15

In a context of high uncertainty about hydro-climatic variables, the development of updated methods for climate impact and adaptation assessment is as important, if not more important than the provision of improved climate change data. In this paper, we introduce a hybrid method to facilitate mainstreaming adaptation of stormwater systems to climate change: i.e., the Mainstreaming method. The Mainstreaming method starts with an analysis of adaptation tipping points (ATPs), which is effect-based. These are points of reference where the magnitude of climate change is such that acceptable technical, environmental, societal or economic standards may be compromised. It extends the ATP analysis to include aspects from a bottom-up approach. The extension concerns the analysis of adaptation opportunities in the stormwater system. The results from both analyses are then used in combination to identify and exploit Adaptation Mainstreaming Moments (AMMs). Use of this method will enhance the understanding of the adaptive potential of stormwater systems. We have applied the proposed hybrid method to the management of flood risk for an urban stormwater system in Dordrecht (the Netherlands). The main finding of this case study is that the application of the Mainstreaming method helps to increase the no-/low-regret character of adaptation for several reasons: it focuses the attention on the most urgent effects of climate change; it is expected to lead to potential cost reductions, since adaptation options can be integrated into infrastructure and building design at an early stage instead of being applied separately; it will lead to the development of area-specific responses, which could not have been developed on a higher scale level; it makes it possible to take account of local values and sensibilities, which contributes to increased public and political support for the adaptive strategies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Sequential causal inference: Application to randomized trials of adaptive treatment strategies

PubMed Central

Dawson, Ree; Lavori, Philip W.

2009-01-01

SUMMARY Clinical trials that randomize subjects to decision algorithms, which adapt treatments over time according to individual response, have gained considerable interest as investigators seek designs that directly inform clinical decision making. We consider designs in which subjects are randomized sequentially at decision points, among adaptive treatment options under evaluation. We present a sequential method to estimate the comparative effects of the randomized adaptive treatments, which are formalized as adaptive treatment strategies. Our causal estimators are derived using Bayesian predictive inference. We use analytical and empirical calculations to compare the predictive estimators to (i) the ‘standard’ approach that allocates the sequentially obtained data to separate strategy-specific groups as would arise from randomizing subjects at baseline; (ii) the semi-parametric approach of marginal mean models that, under appropriate experimental conditions, provides the same sequential estimator of causal differences as the proposed approach. Simulation studies demonstrate that sequential causal inference offers substantial efficiency gains over the standard approach to comparing treatments, because the predictive estimators can take advantage of the monotone structure of shared data among adaptive strategies. We further demonstrate that the semi-parametric asymptotic variances, which are marginal ‘one-step’ estimators, may exhibit significant bias, in contrast to the predictive variances. We show that the conditions under which the sequential method is attractive relative to the other two approaches are those most likely to occur in real studies. PMID:17914714

Participatory design of mass health communication in three languages for seniors and people with disabilities on Medicaid.

PubMed

Neuhauser, Linda; Rothschild, Beccah; Graham, Carrie; Ivey, Susan L; Konishi, Susana

2009-12-01

We used participatory design methods to develop and test guidebooks about health care choices intended for 600 000 English-, Spanish-, and Chinese-speaking seniors and people with disabilities receiving Medicaid in California. Design and testing processes were conducted with consumers and professionals; they included 24 advisory group interviews, 36 usability tests, 18 focus groups (105 participants), 51 key informant interviews, guidebook readability and suitability testing, linguistic adaptation, and iterative revisions of 4 prototypes. Participatory design processes identified preferences of intended audiences for guidebook content, linguistic adaptation, and format; guidebook readability was scored at the sixth- to eighth-grade level and suitability at 95%. These findings informed the design of a separate efficacy study that showed high guidebook usage and satisfaction, and better gains in knowledge, confidence, and intended behaviors among intervention participants than among control participants. Participatory design can be used effectively in mass communication to inform vulnerable audiences of health care choices. The techniques described can be adapted for a broad range of health communication interventions.

Advancements in adaptive aerodynamic technologies for airfoils and wings

NASA Astrophysics Data System (ADS)

Jepson, Jeffrey Keith

Although aircraft operate over a wide range of flight conditions, current fixed-geometry aircraft are optimized for only a few of these conditions. By altering the shape of the aircraft, adaptive aerodynamics can be used to increase the safety and performance of an aircraft by tailoring the aircraft for multiple flight conditions. Of the various shape adaptation concepts currently being studied, the use of multiple trailing-edge flaps along the span of a wing offers a relatively high possibility of being incorporated on aircraft in the near future. Multiple trailing-edge flaps allow for effective spanwise camber adaptation with resulting drag benefits over a large speed range and load alleviation at high-g conditions. The research presented in this dissertation focuses on the development of this concept of using trailing-edge flaps to tailor an aircraft for multiple flight conditions. One of the major tasks involved in implementing trailing-edge flaps is in designing the airfoil to incorporate the flap. The first part of this dissertation presents a design formulation that incorporates aircraft performance considerations in the inverse design of low-speed laminar-flow adaptive airfoils with trailing-edge cruise flaps. The benefit of using adaptive airfoils is that the size of the low-drag region of the drag polar can be effectively increased without increasing the maximum thickness of the airfoil. Two aircraft performance parameters are considered: level-flight maximum speed and maximum range. It is shown that the lift coefficients for the lower and upper corners of the airfoil low-drag range can be appropriately adjusted to tailor the airfoil for these two aircraft performance parameters. The design problem is posed as a part of a multidimensional Newton iteration in an existing conformal-mapping based inverse design code, PROFOIL. This formulation automatically adjusts the lift coefficients for the corners of the low-drag range for a given flap deflection as required for the airfoil-aircraft matching. Examples are presented to illustrate the flapped-airfoil design approach for a general aviation aircraft and the results are validated by comparison with results from post-design aircraft performance computations. Once the airfoil is designed to incorporate a TE flap, it is important to determine the most suitable flap angles along the wing for different flight conditions. The second part of this dissertation presents a method for determining the optimum flap angles to minimize drag based on pressures measured at select locations on the wing. Computational flow simulations using a panel method are used "in the loop" for demonstrating closed-loop control of the flaps. Examples in the paper show that the control algorithm is successful in correctly adapting the wing to achieve the target lift distributions for minimizing induced drag while adjusting the wing angle of attack for operation of the wing in the drag bucket. It is shown that the "sense-and-adapt" approach developed is capable of handling varying and unpredictable inflow conditions. Such a capability could be useful in adapting long-span flexible wings that may experience significant and unknown atmospheric inflow variations along the span. To further develop the "sense-and-adapt" approach, the method was tested experimentally in the third part of the research. The goal of the testing was to see if the same results found computationally can be obtained experimentally. The North Carolina State University subsonic wind tunnel was used for the wind tunnel tests. Results from the testing showed that the "sense-and-adapt" approach has the same performance experimentally as it did computationally. The research presented in this dissertation is a stepping stone towards further development of the concept, which includes modeling the system in the Simulink environment and flight experiments using uninhabited aerial vehicles.

Adaptive optimal training of animal behavior

NASA Astrophysics Data System (ADS)

Bak, Ji Hyun; Choi, Jung Yoon; Akrami, Athena; Witten, Ilana; Pillow, Jonathan

Neuroscience experiments often require training animals to perform tasks designed to elicit various sensory, cognitive, and motor behaviors. Training typically involves a series of gradual adjustments of stimulus conditions and rewards in order to bring about learning. However, training protocols are usually hand-designed, and often require weeks or months to achieve a desired level of task performance. Here we combine ideas from reinforcement learning and adaptive optimal experimental design to formulate methods for efficient training of animal behavior. Our work addresses two intriguing problems at once: first, it seeks to infer the learning rules underlying an animal's behavioral changes during training; second, it seeks to exploit these rules to select stimuli that will maximize the rate of learning toward a desired objective. We develop and test these methods using data collected from rats during training on a two-interval sensory discrimination task. We show that we can accurately infer the parameters of a learning algorithm that describes how the animal's internal model of the task evolves over the course of training. We also demonstrate by simulation that our method can provide a substantial speedup over standard training methods.

Adaptive fuzzy sliding control of single-phase PV grid-connected inverter

PubMed Central

Zhu, Yunkai

2017-01-01

In this paper, an adaptive fuzzy sliding mode controller is proposed to control a two-stage single-phase photovoltaic (PV) grid-connected inverter. Two key technologies are discussed in the presented PV system. An incremental conductance method with adaptive step is adopted to track the maximum power point (MPP) by controlling the duty cycle of the controllable power switch of the boost DC-DC converter. An adaptive fuzzy sliding mode controller with an integral sliding surface is developed for the grid-connected inverter where a fuzzy system is used to approach the upper bound of the system nonlinearities. The proposed strategy has strong robustness for the sliding mode control can be designed independently and disturbances can be adaptively compensated. Simulation results of a PV grid-connected system verify the effectiveness of the proposed method, demonstrating the satisfactory robustness and performance. PMID:28797060

Convergence of fractional adaptive systems using gradient approach.

PubMed

Gallegos, Javier A; Duarte-Mermoud, Manuel A

2017-07-01

Conditions for boundedness and convergence of the output error and the parameter error for various Caputo's fractional order adaptive schemes based on the steepest descent method are derived in this paper. To this aim, the concept of sufficiently exciting signals is introduced, characterized and related to the concept of persistently exciting signals used in the integer order case. An application is designed in adaptive indirect control of integer order systems using fractional equations to adjust parameters. This application is illustrated for a pole placement adaptive problem. Advantages of using fractional adjustment in control adaptive schemes are experimentally obtained. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The Applied Behavior Analysis Research Paradigm and Single-Subject Designs in Adapted Physical Activity Research.

PubMed

Haegele, Justin A; Hodge, Samuel Russell

2015-10-01

There are basic philosophical and paradigmatic assumptions that guide scholarly research endeavors, including the methods used and the types of questions asked. Through this article, kinesiology faculty and students with interests in adapted physical activity are encouraged to understand the basic assumptions of applied behavior analysis (ABA) methodology for conducting, analyzing, and presenting research of high quality in this paradigm. The purposes of this viewpoint paper are to present information fundamental to understanding the assumptions undergirding research methodology in ABA, describe key aspects of single-subject research designs, and discuss common research designs and data-analysis strategies used in single-subject studies.

SERVQUAL Application and Adaptation for Educational Service Quality Assessments in Russian Higher Education

ERIC Educational Resources Information Center

Galeeva, Railya B.

2016-01-01

Purpose: The purpose of this study is to demonstrate an adaptation of the SERVQUAL survey method for measuring the quality of higher educational services in a Russian university context. We use a new analysis and a graphical technique for presentation of results. Design/methodology/approach: The methodology of this research follows the classic…

An Interactive Computer-Aided Instructional Strategy and Assessment Methods for System Identification and Adaptive Control Laboratory

ERIC Educational Resources Information Center

Özbek, Necdet Sinan; Eker, Ilyas

2015-01-01

This study describes a set of real-time interactive experiments that address system identification and model reference adaptive control (MRAC) techniques. In constructing laboratory experiments that contribute to efficient teaching, experimental design and instructional strategy are crucial, but a process for doing this has yet to be defined. This…

Key concepts and methods in social vulnerability and adaptive capacity

Treesearch

Daniel J. Murphy; Carina Wyborn; Laurie Yung; Daniel R. Williams

2015-01-01

National forests have been asked to assess how climate change will impact nearby human communities. To assist their thinking on this topic, we examine the concepts of social vulnerability and adaptive capacity with an emphasis on a range of theoretical and methodological approaches. This analysis is designed to help researchers and decision-makers select appropriate...

Architecture and Design Process of the Individualized Assessment System Integrable to Distance Education Softwares

ERIC Educational Resources Information Center

Ozyurt, Hacer; Ozyurt, Ozcan; Baki, Adnan

2012-01-01

Assessment is one of the methods used for evaluation of the learning outputs. Nowadays, use of adaptive assessment systems estimating ability level and abilities of the students is becoming widespread instead of traditional assessment systems. Adaptive assessment system evaluates students not only according to their marks that they take in test…

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

Laying the Groundwork for NCLEX Success: An Exploration of Adaptive Quizzing as an Examination Preparation Method.

PubMed

Cox-Davenport, Rebecca A; Phelan, Julia C

2015-05-01

First-time NCLEX-RN pass rates are an important indicator of nursing school success and quality. Nursing schools use different methods to anticipate NCLEX outcomes and help prevent student failure and possible threat to accreditation. This study evaluated the impact of a shift in NCLEX preparation policy at a BSN program in the southeast United States. The policy shifted from the use of predictor score thresholds to determine graduation eligibility to a more proactive remediation strategy involving adaptive quizzing. A descriptive correlational design evaluated the impact of an adaptive quizzing system designed to give students ongoing active practice and feedback and explored the relationship between predictor examinations and NCLEX success. Data from student usage of the system as well as scores on predictor tests were collected for three student cohorts. Results revealed a positive correlation between adaptive quizzing system usage and content mastery. Two of the 69 students in the sample did not pass the NCLEX. With so few students failing the NCLEX, predictability of any course variables could not be determined. The power of predictor examinations to predict NCLEX failure could also not be supported. The most consistent factor among students, however, was their content mastery level within the adaptive quizzing system. Implications of these findings are discussed.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

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

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

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.

Adaptive governance good practice: Show me the evidence!

PubMed

Sharma-Wallace, Lisa; Velarde, Sandra J; Wreford, Anita

2018-09-15

Adaptive governance has emerged in the last decade as an intriguing avenue of theory and practice for the holistic management of complex environmental problems. Research on adaptive governance has flourished since the field's inception, probing the process and mechanisms underpinning the new approach while offering various justifications and prescriptions for empirical use. Nevertheless, recent reviews of adaptive governance reveal some important conceptual and practical gaps in the field, particularly concerning challenges in its application to real-world cases. In this paper, we respond directly to the empirical challenge of adaptive governance, specifically asking: which methods contribute to the implementation of successful adaptive governance process and outcomes in practice and across cases and contexts? We adopt a systematic literature review methodology which considers the current body of empirical literature on adaptive governance of social-ecological systems in order to assess and analyse the methods affecting successful adaptive governance practice across the range of existing cases. We find that methods contributing to adaptive governance in practice resemble the design recommendations outlined in previous adaptive governance scholarship, including meaningful collaboration across actors and scales; effective coordination between stakeholders and levels; building social capital; community empowerment and engagement; capacity development; linking knowledge and decision-making through data collection and monitoring; promoting leadership capacity; and exploiting or creating governance opportunities. However, we critically contextualise these methods by analysing and summarising their patterns-in-use, drawing examples from the cases to explore the specific ways they were successfully or unsuccessfully applied to governance issues on-the-ground. Our results indicate some important underlying shared patterns, trajectories, and lessons learned for evidence-based adaptive governance good practice within and across diverse sectors, issues, and contexts. Copyright © 2018. Published by Elsevier Ltd.

Improved neural network based scene-adaptive nonuniformity correction method for infrared focal plane arrays.

PubMed

Lai, Rui; Yang, Yin-tang; Zhou, Duan; Li, Yue-jin

2008-08-20

An improved scene-adaptive nonuniformity correction (NUC) algorithm for infrared focal plane arrays (IRFPAs) is proposed. This method simultaneously estimates the infrared detectors' parameters and eliminates the nonuniformity causing fixed pattern noise (FPN) by using a neural network (NN) approach. In the learning process of neuron parameter estimation, the traditional LMS algorithm is substituted with the newly presented variable step size (VSS) normalized least-mean square (NLMS) based adaptive filtering algorithm, which yields faster convergence, smaller misadjustment, and lower computational cost. In addition, a new NN structure is designed to estimate the desired target value, which promotes the calibration precision considerably. The proposed NUC method reaches high correction performance, which is validated by the experimental results quantitatively tested with a simulative testing sequence and a real infrared image sequence.

Job Analysis and Workplace Design Resources for Rehabilitation.

ERIC Educational Resources Information Center

Priest, John W.; Roessler, Richard T.

1983-01-01

The authors stress the role of the multidisciplinary team in vocational rehabilitation, particularly the industrial engineer, in performing job analysis and workplace design to accommodate disabled persons in industry. Steps to effective job adaptation are charted, and methods of job analysis are discussed. (Author/MC)

Design and landing dynamic analysis of reusable landing leg for a near-space manned capsule

NASA Astrophysics Data System (ADS)

Yue, Shuai; Nie, Hong; Zhang, Ming; Wei, Xiaohui; Gan, Shengyong

2018-06-01

To improve the landing performance of a near-space manned capsule under various landing conditions, a novel landing system is designed that employs double chamber and single chamber dampers in the primary and auxiliary struts, respectively. A dynamic model of the landing system is established, and the damper parameters are determined by employing the design method. A single-leg drop test with different initial pitch angles is then conducted to compare and validate the simulation model. Based on the validated simulation model, seven critical landing conditions regarding nine crucial landing responses are found by combining the radial basis function (RBF) surrogate model and adaptive simulated annealing (ASA) optimization method. Subsequently, the adaptability of the landing system under critical landing conditions is analyzed. The results show that the simulation effectively results match the test results, which validates the accuracy of the dynamic model. In addition, all of the crucial responses under their corresponding critical landing conditions satisfy the design specifications, demonstrating the feasibility of the landing system.

The control of flexible structure vibrations using a cantilevered adaptive truss

NASA Technical Reports Server (NTRS)

Wynn, Robert H., Jr.; Robertshaw, Harry H.

1991-01-01

Analytical and experimental procedures and design tools are presented for the control of flexible structure vibrations using a cantilevered adaptive truss. Simulated and experimental data are examined for three types of structures: a slender beam, a single curved beam, and two curved beams. The adaptive truss is shown to produce a 6,000-percent increase in damping, demonstrating its potential in vibration control. Good agreement is obtained between the simulated and experimental data, thus validating the modeling methods.

Super-Gaussian laser intensity output formation by means of adaptive optics

NASA Astrophysics Data System (ADS)

Cherezova, T. Y.; Chesnokov, S. S.; Kaptsov, L. N.; Kudryashov, A. V.

1998-10-01

An optical resonator using an intracavity adaptive mirror with three concentric rings of controlling electrodes, which produc low loss and large beamwidth super-Gaussian output of order 4, 6, 8, is analyzed. An inverse propagation method is used to determine the appropriate shape of the adaptive mirror. The mirror reproduces the shape with minimal RMS error by combining weights of experimentally measured response functions of the mirror sample. The voltages applied to each mirror electrode are calculated. Practical design parameters such as construction of an adaptive mirror, Fresnel numbers, and geometric factor are discussed.

Mixture-based gatekeeping procedures in adaptive clinical trials.

PubMed

Kordzakhia, George; Dmitrienko, Alex; Ishida, Eiji

2018-01-01

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to "multivariate" multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.

The Co-simulation of Humanoid Robot Based on Solidworks, ADAMS and Simulink

NASA Astrophysics Data System (ADS)

Song, Dalei; Zheng, Lidan; Wang, Li; Qi, Weiwei; Li, Yanli

A simulation method of adaptive controller is proposed for the humanoid robot system based on co-simulation of Solidworks, ADAMS and Simulink. A complex mathematical modeling process is avoided by this method, and the real time dynamic simulating function of Simulink would be exerted adequately. This method could be generalized to other complicated control system. This method is adopted to build and analyse the model of humanoid robot. The trajectory tracking and adaptive controller design also proceed based on it. The effect of trajectory tracking is evaluated by fitting-curve theory of least squares method. The anti-interference capability of the robot is improved a lot through comparative analysis.

An Adaptive Staggered Dose Design for a Normal Endpoint.

PubMed

Wu, Joseph; Menon, Sandeep; Chang, Mark

2015-01-01

In a clinical trial where several doses are compared to a control, a multi-stage design that combines both the selection of the best dose and the confirmation of this selected dose is desirable. An example is the two-stage drop-the-losers or pick-the-winner design, where inferior doses are dropped after interim analysis. Selection of target dose(s) can be based on ranking of observed effects, hypothesis testing with adjustment for multiplicity, or other criteria at interim stages. A number of methods have been proposed and have made significant gains in trial efficiency. However, many of these designs started off with all doses with equal allocation and did not consider prioritizing the doses using existing dose-response information. We propose an adaptive staggered dose procedure that allows explicit prioritization of doses and applies error spending scheme that favors doses with assumed better responses. This design starts off with only a subset of the doses and adaptively adds new doses depending on interim results. Using simulation, we have shown that this design performs better in terms of increased statistical power than the drop-the-losers design given strong prior information of dose response.

Adapting Cognitive Walkthrough to Support Game Based Learning Design

ERIC Educational Resources Information Center

Farrell, David; Moffat, David C.

2014-01-01

For any given Game Based Learning (GBL) project to be successful, the player must learn something. Designers may base their work on pedagogical research, but actual game design is still largely driven by intuition. People are famously poor at unsupported methodical thinking and relying so much on instinct is an obvious weak point in GBL design…

SVAS3: Strain Vector Aided Sensorization of Soft Structures

PubMed Central

Culha, Utku; Nurzaman, Surya G.; Clemens, Frank; Iida, Fumiya

2014-01-01

Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations. PMID:25036332

Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems.

PubMed

Lijun Long; Jun Zhao

2017-04-01

In this paper, for a class of switched large-scale uncertain nonlinear systems with unknown control coefficients and unmeasurable states, a switched-dynamic-surface-based decentralized adaptive neural output-feedback control approach is developed. The approach proposed extends the classical dynamic surface control (DSC) technique for nonswitched version to switched version by designing switched first-order filters, which overcomes the problem of multiple "explosion of complexity." Also, a dual common coordinates transformation of all subsystems is exploited to avoid individual coordinate transformations for subsystems that are required when applying the backstepping recursive design scheme. Nussbaum-type functions are utilized to handle the unknown control coefficients, and a switched neural network observer is constructed to estimate the unmeasurable states. Combining with the average dwell time method and backstepping and the DSC technique, decentralized adaptive neural controllers of subsystems are explicitly designed. It is proved that the approach provided can guarantee the semiglobal uniformly ultimately boundedness for all the signals in the closed-loop system under a class of switching signals with average dwell time, and the tracking errors to a small neighborhood of the origin. A two inverted pendulums system is provided to demonstrate the effectiveness of the method proposed.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

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

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

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

Methods for the cultural adaptation of a diabetes lifestyle intervention for Latinas: an illustrative project.

PubMed

Osuna, Diego; Barrera, Manuel; Strycker, Lisa A; Toobert, Deborah J; Glasgow, Russell E; Geno, Cristy R; Almeida, Fabio; Perdomo, Malena; King, Diane; Doty, Alyssa Tinley

2011-05-01

Because Latinas experience a high prevalence of type 2 diabetes and its complications, there is an urgent need to reach them with interventions that promote healthful lifestyles. This article illustrates a sequential approach that took an effective multiple-risk-factor behavior-change program and adapted it for Latinas with type 2 diabetes. Adaptation stages include (a) information gathering from literature and focus groups, (b) preliminary adaptation design, and (c) preliminary adaptation test. In this third stage, a pilot study finds that participants were highly satisfied with the intervention and showed improvement across diverse outcomes. Key implications for applications include the importance of a model for guiding cultural adaptations, and the value of procedures for obtaining continuous feedback from staff and participants during the preliminary adaptation test.

Adapted Intervention Mapping: A Strategic Planning Process for Increasing Physical Activity and Healthy Eating Opportunities in Schools via Environment and Policy Change

ERIC Educational Resources Information Center

Belansky, Elaine S.; Cutforth, Nick; Chavez, Robert; Crane, Lori A.; Waters, Emily; Marshall, Julie A.

2013-01-01

Background: School environment and policy changes have increased healthy eating and physical activity; however, there has been modest success in translating research ?ndings to practice. The School Environment Project tested whether an adapted version of Intervention Mapping (AIM) resulted in school change. Methods: Using a pair randomized design,…

Condition Based Maintenance Technology Impact Study: Assessment Methods, Study Design and Interim Results

DTIC Science & Technology

2014-07-01

Unified Theory of Acceptance and Use of Technology, Structuration Model of Technology, UNCLASSIFIED DSTO-TR-2992 UNCLASSIFIED 5 Adaptive...Structuration Theory , Model of Mutual Adaptation, Model of Technology Appropriation, Diffusion/Implementation Model, and Tri-core Model, among others [11...simulation gaming essay/scenario writing genius forecasting role play/acting backcasting swot brainstorming relevance tree/logic chart scenario workshop

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Psychosocial Adaptation to Visual Impairment and Its Relationship to Depressive Affect in Older Adults with Age-Related Macular Degeneration

ERIC Educational Resources Information Center

Tolman, Jennifer; Hill, Robert D.; Kleinschmidt, Julia J.; Gregg, Charles H.

2005-01-01

Purpose: In this study we examined psychosocial adaptation to vision loss and its relationship to depressive symptomatology in legally blind older adults with age-related macular degeneration (ARMD). Design and Methods: The 144 study participants were outpatients of a large regional vision clinic that specializes in the diagnosis and treatment of…

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

Passive activity observation (PAO) method to estimate outdoor thermal adaptation in public space: case studies in Australian cities.

PubMed

Sharifi, Ehsan; Boland, John

2018-06-18

Outdoor thermal comfort is influenced by people's climate expectations, perceptions and adaptation capacity. Varied individual response to comfortable or stressful thermal environments results in a deviation between actual outdoor thermal activity choices and those predicted by thermal comfort indices. This paper presents a passive activity observation (PAO) method for estimating contextual limits of outdoor thermal adaptation. The PAO method determines which thermal environment result in statistically meaningful changes may occur in outdoor activity patterns, and it estimates thresholds of outdoor thermal neutrality and limits of thermal adaptation in public space based on activity observation and microclimate field measurement. Applications of the PAO method have been demonstrated in Adelaide, Melbourne and Sydney, where outdoor activities were analysed against outdoor thermal comfort indices between 2013 and 2014. Adjusted apparent temperature (aAT), adaptive predicted mean vote (aPMV), outdoor standard effective temperature (OUT_SET), physiological equivalent temperature (PET) and universal thermal comfort index (UTCI) are calculated from the PAO data. Using the PAO method, the high threshold of outdoor thermal neutrality was observed between 24 °C for optional activities and 34 °C for necessary activities (UTCI scale). Meanwhile, the ultimate limit of thermal adaptation in uncontrolled public spaces is estimated to be between 28 °C for social activities and 48 °C for necessary activities. Normalised results indicate that city-wide high thresholds for outdoor thermal neutrality vary from 25 °C in Melbourne to 26 °C in Sydney and 30 °C in Adelaide. The PAO method is a relatively fast and localised method for measuring limits of outdoor thermal adaptation and effectively informs urban design and policy making in the context of climate change.

H-P adaptive methods for finite element analysis of aerothermal loads in high-speed flows

NASA Technical Reports Server (NTRS)

Chang, H. J.; Bass, J. M.; Tworzydlo, W.; Oden, J. T.

1993-01-01

The commitment to develop the National Aerospace Plane and Maneuvering Reentry Vehicles has generated resurgent interest in the technology required to design structures for hypersonic flight. The principal objective of this research and development effort has been to formulate and implement a new class of computational methodologies for accurately predicting fine scale phenomena associated with this class of problems. The initial focus of this effort was to develop optimal h-refinement and p-enrichment adaptive finite element methods which utilize a-posteriori estimates of the local errors to drive the adaptive methodology. Over the past year this work has specifically focused on two issues which are related to overall performance of a flow solver. These issues include the formulation and implementation (in two dimensions) of an implicit/explicit flow solver compatible with the hp-adaptive methodology, and the design and implementation of computational algorithm for automatically selecting optimal directions in which to enrich the mesh. These concepts and algorithms have been implemented in a two-dimensional finite element code and used to solve three hypersonic flow benchmark problems (Holden Mach 14.1, Edney shock on shock interaction Mach 8.03, and the viscous backstep Mach 4.08).

Optical Design for Extremely Large Telescope Adaptive Optics Systems

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

Bauman, Brian J.

2003-01-01

Designing an adaptive optics (AO) system for extremely large telescopes (ELT's) will present new optical engineering challenges. Several of these challenges are addressed in this work, including first-order design of multi-conjugate adaptive optics (MCAO) systems, pyramid wavefront sensors (PWFS's), and laser guide star (LGS) spot elongation. MCAO systems need to be designed in consideration of various constraints, including deformable mirror size and correction height. The y,{bar y} method of first-order optical design is a graphical technique that uses a plot with marginal and chief ray heights as coordinates; the optical system is represented as a segmented line. This method ismore » shown to be a powerful tool in designing MCAO systems. From these analyses, important conclusions about configurations are derived. PWFS's, which offer an alternative to Shack-Hartmann (SH) wavefront sensors (WFS's), are envisioned as the workhorse of layer-oriented adaptive optics. Current approaches use a 4-faceted glass pyramid to create a WFS analogous to a quad-cell SH WFS. PWFS's and SH WFS's are compared and some newly-considered similarities and PWFS advantages are presented. Techniques to extend PWFS's are offered: First, PWFS's can be extended to more pixels in the image by tiling pyramids contiguously. Second, pyramids, which are difficult to manufacture, can be replaced by less expensive lenslet arrays. An approach is outlined to convert existing SH WFS's to PWFS's for easy evaluation of PWFS's. Also, a demonstration of PWFS's in sensing varying amounts of an aberration is presented. For ELT's, the finite altitude and finite thickness of LGS's means that the LGS will appear elongated from the viewpoint of subapertures not directly under the telescope. Two techniques for dealing with LGS spot elongation in SH WFS's are presented. One method assumes that the laser will be pulsed and uses a segmented micro-electromechanical system (MEMS) to track the LGS light subaperture by subaperture as the light is returned from the upward-propagating laser pulse. A second method can be used if the laser is not pulsed. A lenslet array is described which creates ''pixels'' which are aligned with the axes of the elongated spot of each subaperture, without requiring special charge-coupled devices (CCD's).« less

Fostering Healthy Futures for Teens: Adaptation of an Evidence-Based Program

PubMed Central

Taussig, Heather; Weiler, Lindsey; Rhodes, Tara; Hambrick, Erin; Wertheimer, Robyn; Fireman, Orah; Combs, Melody

2015-01-01

Objective This article describes the process of adapting and implementing a complex, multicomponent intervention for a new population. Specifically, the article delineates the development and implementation of the Fostering Healthy Futures for Teens (FHF-T) program, which is an adaptation and extension of the Fostering Healthy Futures® (FHF) preventive intervention. FHF is a 9-month mentoring and skills group program for 9 to 11 year olds recently placed in foster care. Following the designation of FHF as an evidence-based intervention, there was increasing demand for the program. However, the narrow population for which FHF had demonstrated efficacy limited broader implementation of the existing intervention. FHF-T was designed to extend the reach of the program by adapting the FHF intervention for adolescents in the early years of high school who have a history of out-of-home care. Specifically, this adaptation recognizes key developmental differences between preadolescent and adolescent populations. Method After designing a program model and adapting the program components, the FHF-T mentoring program was implemented with 42 youth over 2 program years. Results Of the teens who were offered the program, 75% chose to enroll, and 88% of those graduated 9 months later. Although the program evidenced high rates of uptake and participant satisfaction, some unexpected challenges were encountered that will need to be addressed in future iterations of the program. Conclusions Too often program adaptations are made without careful consideration of important contextual issues, and too infrequently, these adapted programs are studied. Our process of program adaptation with rigorous measurement of program implementation provides a useful model for other evidence-based programs seeking thoughtful adaptation. PMID:27019678

Design of all-weather celestial navigation system

NASA Astrophysics Data System (ADS)

Sun, Hongchi; Mu, Rongjun; Du, Huajun; Wu, Peng

2018-03-01

In order to realize autonomous navigation in the atmosphere, an all-weather celestial navigation system is designed. The research of celestial navigation system include discrimination method of comentropy and the adaptive navigation algorithm based on the P value. The discrimination method of comentropy is studied to realize the independent switching of two celestial navigation modes, starlight and radio. Finally, an adaptive filtering algorithm based on P value is proposed, which can greatly improve the disturbance rejection capability of the system. The experimental results show that the accuracy of the three axis attitude is better than 10″, and it can work all weather. In perturbation environment, the position accuracy of the integrated navigation system can be increased 20% comparing with the traditional method. It basically meets the requirements of the all-weather celestial navigation system, and it has the ability of stability, reliability, high accuracy and strong anti-interference.

Adaptive output-based command shaping for sway control of a 3D overhead crane with payload hoisting and wind disturbance

NASA Astrophysics Data System (ADS)

Abdullahi, Auwalu M.; Mohamed, Z.; Selamat, H.; Pota, Hemanshu R.; Zainal Abidin, M. S.; Ismail, F. S.; Haruna, A.

2018-01-01

Payload hoisting and wind disturbance during crane operations are among the challenging factors that affect a payload sway and thus, affect the crane's performance. This paper proposes a new online adaptive output-based command shaping (AOCS) technique for an effective payload sway reduction of an overhead crane under the influence of those effects. This technique enhances the previously developed output-based command shaping (OCS) which was effective only for a fixed system and without external disturbances. Unlike the conventional input shaping design technique which requires the system's natural frequency and damping ratio, the proposed technique is designed by using the output signal and thus, an online adaptive algorithm can be formulated. To test the effectiveness of the AOCS, experiments are carried out using a laboratory overhead crane with a payload hoisting in the presence of wind, and with different payloads. The superiority of the method is confirmed by 82% and 29% reductions in the overall sway and the maximum transient sway respectively, when compared to the OCS, and two robust input shapers namely Zero Vibration Derivative-Derivative and Extra-Insensitive shapers. Furthermore, the method demonstrates a uniform crane's performance under all conditions. It is envisaged that the proposed method can be very useful in designing an effective controller for a crane system with an unknown payload and under the influence of external disturbances.

Designing Glass Panels for Economy and Reliability

NASA Technical Reports Server (NTRS)

Moore, D. M.

1983-01-01

Analytical method determines probability of failure of rectangular glass plates subjected to uniformly distributed loads such as those from wind, earthquake, snow, and deadweight. Developed as aid in design of protective glass covers for solar-cell arrays and solar collectors, method is also useful in estimating the reliability of large windows in buildings exposed to high winds and is adapted to nonlinear stress analysis of simply supported plates of any elastic material.

Development of adaptive bust for female soft body armour using three dimensional (3D) warp interlock fabrics: Three dimensional (3D) design process

NASA Astrophysics Data System (ADS)

Abtew, M. A.; Bruniaux, P.; Boussu, F.

2017-10-01

The traditional two dimensional (2D) pattern making method for developing female body armour has a negative effect on the ballistic protective performance as well as the comfort of the wearer. This is due to, unlike the male body armour, the female body armour manufacturing involves different darts to accommodate the natural curvature of the female body, i.e. bust area, which will reveals the weak parts at the seam and stitch area while ballistic impact. Moreover, the proper bra size also plays an important role not only in bra design but also in the design of a women’s ballistic vest. The present research study tried to propose the novel 3D designing approach for developing different volumes of breast using feature points (both bust surface and outline points) in the specific 3D adaptive mannequin. Later the flattened 3D bra patterns of this method has been also compare with the 2D standard pattern making in order to modify and match with 2D traditional method. The result indicated that the proposed method which conceives the 3D patterns on the 3D bust is easier to implement and can generate patterns with satisfactory fit and comfort as compared to 2D patterns.

The advantages and limitations of guideline adaptation frameworks.

PubMed

Wang, Zhicheng; Norris, Susan L; Bero, Lisa

2018-05-29

The implementation of evidence-based guidelines can improve clinical and public health outcomes by helping health professionals practice in the most effective manner, as well as assisting policy-makers in designing optimal programs. Adaptation of a guideline to suit the context in which it is intended to be applied can be a key step in the implementation process. Without taking the local context into account, certain interventions recommended in evidence-based guidelines may be infeasible under local conditions. Guideline adaptation frameworks provide a systematic way of approaching adaptation, and their use may increase transparency, methodological rigor, and the quality of the adapted guideline. This paper presents a number of adaptation frameworks that are currently available. We aim to compare the advantages and limitations of their processes, methods, and resource implications. These insights into adaptation frameworks can inform the future development of guidelines and systematic methods to optimize their adaptation. Recent adaptation frameworks show an evolution from adapting entire existing guidelines, to adapting specific recommendations extracted from an existing guideline, to constructing evidence tables for each recommendation that needs to be adapted. This is a move towards more recommendation-focused, context-specific processes and considerations. There are still many gaps in knowledge about guideline adaptation. Most of the frameworks reviewed lack any evaluation of the adaptation process and outcomes, including user satisfaction and resources expended. The validity, usability, and health impact of guidelines developed via an adaptation process have not been studied. Lastly, adaptation frameworks have not been evaluated for use in low-income countries. Despite the limitations in frameworks, a more systematic approach to adaptation based on a framework is valuable, as it helps to ensure that the recommendations stay true to the evidence while taking local needs into account. The utilization of frameworks in the guideline implementation process can be optimized by increasing the understanding and upfront estimation of resource and time needed, capacity building in adaptation methods, and increasing the adaptability of the source recommendation document.

Digital controllers for VTOL aircraft

NASA Technical Reports Server (NTRS)

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

1976-01-01

Using linear-optimal estimation and control techniques, digital-adaptive control laws have been designed for a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for non-zero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

Policy Tree Optimization for Adaptive Management of Water Resources Systems

NASA Astrophysics Data System (ADS)

Herman, J. D.; Giuliani, M.

2016-12-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points", which are threshold values of indicator variables that signal a change in policy. However, there remains a need for a general method to optimize the choice of indicators and their threshold values in a way that is easily interpretable for decision makers. Here we propose a conceptual framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. We demonstrate the approach using Folsom Reservoir, California as a case study, in which operating policies must balance the risk of both floods and droughts. Given a set of feature variables, such as reservoir level, inflow observations and forecasts, and time of year, the resulting policy defines the conditions under which flood control and water supply hedging operations should be triggered. Importantly, the tree-based rule sets are easy to interpret for decision making, and can be compared to historical operating policies to understand the adaptations needed under possible climate change scenarios. Several remaining challenges are discussed, including the empirical convergence properties of the method, and extensions to irreversible decisions such as infrastructure. Policy tree optimization, and corresponding open-source software, provide a generalizable, interpretable approach to designing adaptive policies under uncertainty for water resources systems.

Real-Time Adaptive Control of a Magnetic Levitation System with a Large Range of Load Disturbance.

PubMed

Zhang, Zhizhou; Li, Xiaolong

2018-05-11

In an idle light-load or a full-load condition, the change of the load mass of a suspension system is very significant. If the control parameters of conventional control methods remain unchanged, the suspension performance of the control system deteriorates rapidly or even loses stability when the load mass changes in a large range. In this paper, a real-time adaptive control method for a magnetic levitation system with large range of mass changes is proposed. First, the suspension control system model of the maglev train is built up, and the stability of the closed-loop system is analyzed. Then, a fast inner current-loop is used to simplify the design of the suspension control system, and an adaptive control method is put forward to ensure that the system is still in a stable state when the load mass varies in a wide range. Simulations and experiments show that when the load mass of the maglev system varies greatly, the adaptive control method is effective to suspend the system stably with a given displacement.

Real-Time Adaptive Control of a Magnetic Levitation System with a Large Range of Load Disturbance

PubMed Central

Zhang, Zhizhou; Li, Xiaolong

2018-01-01

In an idle light-load or a full-load condition, the change of the load mass of a suspension system is very significant. If the control parameters of conventional control methods remain unchanged, the suspension performance of the control system deteriorates rapidly or even loses stability when the load mass changes in a large range. In this paper, a real-time adaptive control method for a magnetic levitation system with large range of mass changes is proposed. First, the suspension control system model of the maglev train is built up, and the stability of the closed-loop system is analyzed. Then, a fast inner current-loop is used to simplify the design of the suspension control system, and an adaptive control method is put forward to ensure that the system is still in a stable state when the load mass varies in a wide range. Simulations and experiments show that when the load mass of the maglev system varies greatly, the adaptive control method is effective to suspend the system stably with a given displacement. PMID:29751610

Design of a real-time system of moving ship tracking on-board based on FPGA in remote sensing images

NASA Astrophysics Data System (ADS)

Yang, Tie-jun; Zhang, Shen; Zhou, Guo-qing; Jiang, Chuan-xian

2015-12-01

With the broad attention of countries in the areas of sea transportation and trade safety, the requirements of efficiency and accuracy of moving ship tracking are becoming higher. Therefore, a systematic design of moving ship tracking onboard based on FPGA is proposed, which uses the Adaptive Inter Frame Difference (AIFD) method to track a ship with different speed. For the Frame Difference method (FD) is simple but the amount of computation is very large, it is suitable for the use of FPGA to implement in parallel. But Frame Intervals (FIs) of the traditional FD method are fixed, and in remote sensing images, a ship looks very small (depicted by only dozens of pixels) and moves slowly. By applying invariant FIs, the accuracy of FD for moving ship tracking is not satisfactory and the calculation is highly redundant. So we use the adaptation of FD based on adaptive extraction of key frames for moving ship tracking. A FPGA development board of Xilinx Kintex-7 series is used for simulation. The experiments show that compared with the traditional FD method, the proposed one can achieve higher accuracy of moving ship tracking, and can meet the requirement of real-time tracking in high image resolution.

Integration of Monte-Carlo ray tracing with a stochastic optimisation method: application to the design of solar receiver geometry.

PubMed

Asselineau, Charles-Alexis; Zapata, Jose; Pye, John

2015-06-01

A stochastic optimisation method adapted to illumination and radiative heat transfer problems involving Monte-Carlo ray-tracing is presented. A solar receiver shape optimisation case study illustrates the advantages of the method and its potential: efficient receivers are identified using a moderate computational cost.

Lightweight Adaptation of Classifiers to Users and Contexts: Trends of the Emerging Domain

PubMed Central

Vildjiounaite, Elena; Gimel'farb, Georgy; Kyllönen, Vesa; Peltola, Johannes

2015-01-01

Intelligent computer applications need to adapt their behaviour to contexts and users, but conventional classifier adaptation methods require long data collection and/or training times. Therefore classifier adaptation is often performed as follows: at design time application developers define typical usage contexts and provide reasoning models for each of these contexts, and then at runtime an appropriate model is selected from available ones. Typically, definition of usage contexts and reasoning models heavily relies on domain knowledge. However, in practice many applications are used in so diverse situations that no developer can predict them all and collect for each situation adequate training and test databases. Such applications have to adapt to a new user or unknown context at runtime just from interaction with the user, preferably in fairly lightweight ways, that is, requiring limited user effort to collect training data and limited time of performing the adaptation. This paper analyses adaptation trends in several emerging domains and outlines promising ideas, proposed for making multimodal classifiers user-specific and context-specific without significant user efforts, detailed domain knowledge, and/or complete retraining of the classifiers. Based on this analysis, this paper identifies important application characteristics and presents guidelines to consider these characteristics in adaptation design. PMID:26473165

Implementing Culture Change in Nursing Homes: An Adaptive Leadership Framework

PubMed Central

Corazzini, Kirsten; Twersky, Jack; White, Heidi K.; Buhr, Gwendolen T.; McConnell, Eleanor S.; Weiner, Madeline; Colón-Emeric, Cathleen S.

2015-01-01

Purpose of the Study: To describe key adaptive challenges and leadership behaviors to implement culture change for person-directed care. Design and Methods: The study design was a qualitative, observational study of nursing home staff perceptions of the implementation of culture change in each of 3 nursing homes. We conducted 7 focus groups of licensed and unlicensed nursing staff, medical care providers, and administrators. Questions explored perceptions of facilitators and barriers to culture change. Using a template organizing style of analysis with immersion/crystallization, themes of barriers and facilitators were coded for adaptive challenges and leadership. Results: Six key themes emerged, including relationships, standards and expectations, motivation and vision, workload, respect of personhood, and physical environment. Within each theme, participants identified barriers that were adaptive challenges and facilitators that were examples of adaptive leadership. Commonly identified challenges were how to provide person-directed care in the context of extant rules or policies or how to develop staff motivated to provide person-directed care. Implications: Implementing culture change requires the recognition of adaptive challenges for which there are no technical solutions, but which require reframing of norms and expectations, and the development of novel and flexible solutions. Managers and administrators seeking to implement person-directed care will need to consider the role of adaptive leadership to address these adaptive challenges. PMID:24451896

Stochastic Methods for Aircraft Design

NASA Technical Reports Server (NTRS)

Pelz, Richard B.; Ogot, Madara

1998-01-01

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

Combined shape and topology optimization for minimization of maximal von Mises stress

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

Lian, Haojie; Christiansen, Asger N.; Tortorelli, Daniel A.

Here, this work shows that a combined shape and topology optimization method can produce optimal 2D designs with minimal stress subject to a volume constraint. The method represents the surface explicitly and discretizes the domain into a simplicial complex which adapts both structural shape and topology. By performing repeated topology and shape optimizations and adaptive mesh updates, we can minimize the maximum von Mises stress using the p-norm stress measure with p-values as high as 30, provided that the stress is calculated with sufficient accuracy.

Combined shape and topology optimization for minimization of maximal von Mises stress

DOE PAGES

Lian, Haojie; Christiansen, Asger N.; Tortorelli, Daniel A.; ...

2017-01-27

Here, this work shows that a combined shape and topology optimization method can produce optimal 2D designs with minimal stress subject to a volume constraint. The method represents the surface explicitly and discretizes the domain into a simplicial complex which adapts both structural shape and topology. By performing repeated topology and shape optimizations and adaptive mesh updates, we can minimize the maximum von Mises stress using the p-norm stress measure with p-values as high as 30, provided that the stress is calculated with sufficient accuracy.

A new modelling approach for zooplankton behaviour

NASA Astrophysics Data System (ADS)

Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.

We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.

Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces

NASA Astrophysics Data System (ADS)

Song, Qi; Song, Y. D.; Cai, Wenchuan

2011-09-01

Although backstepping control design approach has been widely utilised in many practical systems, little effort has been made in applying this useful method to train systems. The main purpose of this paper is to apply this popular control design technique to speed and position tracking control of high-speed trains. By integrating adaptive control with backstepping control, we develop a control scheme that is able to address not only the traction and braking dynamics ignored in most existing methods, but also the uncertain friction and aerodynamic drag forces arisen from uncertain resistance coefficients. As such, the resultant control algorithms are able to achieve high precision train position and speed tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations.

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 parameter initialization. Finally, the architecture extended control to tasks beyond those used for CLDA training. These results have significant implications towards the development of clinically-viable neuroprosthetics. PMID:27035820

The energy-efficient implementation of an adaptive-filtering-based QRS complex detection method for wearable devices

NASA Astrophysics Data System (ADS)

Tian, Shudong; Han, Jun; Yang, Jianwei; Zeng, Xiaoyang

2017-10-01

Electrocardiogram (ECG) can be used as a valid way for diagnosing heart disease. To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost, two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal, respectively. The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%, tested under the MIT-BIH ECG database. The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation. Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09 × 10 5 μm2, respectively. Project supported by the National Natural Science Foundation of China (Nos. 61574040, 61234002, 61525401).

The Relationship between Parent Report of Adaptive Behavior and Direct Assessment of Reading Ability in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Arciuli. Joanne; Stevens, Kirsten; Trembath, David; Simpson, Ian Craig

2013-01-01

Purpose: This study was designed to shed light on the profile of reading ability in children with autism spectrum disorder (ASD). A key aim was to examine the relationship between parent report of adaptive behavior and direct assessment of reading ability in these children. Method: The authors investigated children's reading ability using the Wide…

A community based approach to improving resilience of forests and water resources: A local and regional climate adaptation methodology

Treesearch

Toby Thaler; Gwen Griffith; Nancy Gilliam

2014-01-01

Forest-based ecosystem services are at risk from human-caused stressors, including climate change. Improving governance and management of forests to reduce impacts and increase community resilience to all stressors is the objective of forest-related climate change adaptation. The Model Forest Policy Program (MFPP) has applied one method designed to meet this objective...

Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

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

Xiu, Dongbin

2017-03-03

The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

Biology-Inspired Autonomous Control

DTIC Science & Technology

2011-08-31

from load sensing in a turbulent flow field with high levels of plant uncertainty and optical feedback latency. The results of this paper suggest... Mimicry of biological systems, in the form of precise mathematical or physical dynamical modeling, is yielding impressive insight into the underlying...processing and plants , the aerospace industry has been slow to accept adaptive control. In the past decade however, newer methods for design of adaptive

Computer Based Porosity Design by Multi Phase Topology Optimization

NASA Astrophysics Data System (ADS)

Burblies, Andreas; Busse, Matthias

2008-02-01

A numerical simulation technique called Multi Phase Topology Optimization (MPTO) based on finite element method has been developed and refined by Fraunhofer IFAM during the last five years. MPTO is able to determine the optimum distribution of two or more different materials in components under thermal and mechanical loads. The objective of optimization is to minimize the component's elastic energy. Conventional topology optimization methods which simulate adaptive bone mineralization have got the disadvantage that there is a continuous change of mass by growth processes. MPTO keeps all initial material concentrations and uses methods adapted from molecular dynamics to find energy minimum. Applying MPTO to mechanically loaded components with a high number of different material densities, the optimization results show graded and sometimes anisotropic porosity distributions which are very similar to natural bone structures. Now it is possible to design the macro- and microstructure of a mechanical component in one step. Computer based porosity design structures can be manufactured by new Rapid Prototyping technologies. Fraunhofer IFAM has applied successfully 3D-Printing and Selective Laser Sintering methods in order to produce very stiff light weight components with graded porosities calculated by MPTO.

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

Influence of each Zernike aberration on the propagation of laser beams through atmospheric turbulence

NASA Astrophysics Data System (ADS)

Azarian, Adrian; Gladysz, Szymon

2014-10-01

We study the influence of each Zernike mode on the propagation of a laser beam through the atmosphere by two different numerical methods. In the first method, an idealized adaptive optics system is modeled to subtract a certain number of Zernike modes from the beam. The effect of each aberration is quantified using the Strehl ratio of the longterm exposure in target/receiver plane. In the second method, the strength of each Zernike mode is varied using a numerical space-filling design during the generation of the phase screens. The resulting central intensity for each point of the design is then studied by a linear discriminant analysis, which yields to the importance of each Zernike mode. The results of the two methods are consistent. They indicate that, for a focused Gaussian beam and for certain geometries and turbulence strengths, the hypothesis of diminishing gains with correction of each new mode is not true. For such cases, we observe jumps in the calculated criteria, which indicate an increased importance of some particular modes, especially coma. The implications of these results for the design of adaptive optics systems are discussed.

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

Adaptive design of an X-ray magnetic circular dichroism spectroscopy experiment with Gaussian process modelling

NASA Astrophysics Data System (ADS)

Ueno, Tetsuro; Hino, Hideitsu; Hashimoto, Ai; Takeichi, Yasuo; Sawada, Masahiro; Ono, Kanta

2018-01-01

Spectroscopy is a widely used experimental technique, and enhancing its efficiency can have a strong impact on materials research. We propose an adaptive design for spectroscopy experiments that uses a machine learning technique to improve efficiency. We examined X-ray magnetic circular dichroism (XMCD) spectroscopy for the applicability of a machine learning technique to spectroscopy. An XMCD spectrum was predicted by Gaussian process modelling with learning of an experimental spectrum using a limited number of observed data points. Adaptive sampling of data points with maximum variance of the predicted spectrum successfully reduced the total data points for the evaluation of magnetic moments while providing the required accuracy. The present method reduces the time and cost for XMCD spectroscopy and has potential applicability to various spectroscopies.

Adaptive filter design using recurrent cerebellar model articulation controller.

PubMed

Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S

2010-07-01

A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.

A Solution Adaptive Technique Using Tetrahedral Unstructured Grids

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2000-01-01

An adaptive unstructured grid refinement technique has been developed and successfully applied to several three dimensional inviscid flow test cases. The method is based on a combination of surface mesh subdivision and local remeshing of the volume grid Simple functions of flow quantities are employed to detect dominant features of the flowfield The method is designed for modular coupling with various error/feature analyzers and flow solvers. Several steady-state, inviscid flow test cases are presented to demonstrate the applicability of the method for solving practical three-dimensional problems. In all cases, accurate solutions featuring complex, nonlinear flow phenomena such as shock waves and vortices have been generated automatically and efficiently.

Optomechanical design and analysis of a self-adaptive mounting method for optimizing phase matching of large potassium dihydrogen phosphate converter

NASA Astrophysics Data System (ADS)

Zhang, Zheng; Tian, Menjiya; Quan, Xusong; Pei, Guoqing; Wang, Hui; Liu, Tianye; Long, Kai; Xiong, Zhao; Rong, Yiming

2017-11-01

Surface control and phase matching of large laser conversion optics are urgent requirements and huge challenges in high-power solid-state laser facilities. A self-adaptive, nanocompensating mounting configuration of a large aperture potassium dihydrogen phosphate (KDP) frequency doubler is proposed based on a lever-type surface correction mechanism. A mechanical, numerical, and optical model is developed and employed to evaluate comprehensive performance of this mounting method. The results validate the method's advantages of surface adjustment and phase matching improvement. In addition, the optimal value of the modulation force is figured out through a series of simulations and calculations.

Adaptive controller for a strength testbed for aircraft structures

NASA Astrophysics Data System (ADS)

Laperdin, A. I.; Yurkevich, V. D.

2017-07-01

The problem of control system design for a strength testbed of aircraft structures is considered. A method for calculating the parameters of a proportional-integral controller (control algorithm) using the time-scale separation method for the testbed taking into account the dead time effect in the control loop is presented. An adaptive control algorithm structure is proposed which limits the amplitude of high-frequency oscillations in the control system with a change in the direction of motion of the rod of the hydraulic cylinders and provides the desired accuracy and quality of transients at all stages of structural loading history. The results of tests of the developed control system with the adaptive control algorithm on an experimental strength testbed for aircraft structures are given.

Observer-based adaptive backstepping control for fractional order systems with input saturation.

PubMed

Sheng, Dian; Wei, Yiheng; Cheng, Songsong; Wang, Yong

2017-07-03

An observer-based fractional order anti-saturation adaptive backstepping control scheme is proposed for incommensurate fractional order systems with input saturation and partial measurable state in this paper. On the basis of stability analysis, a novel state observer is established first since the only information we could acquire is the system output. In order to compensate the saturation, a series of virtual signals are generated via the construction of fractional order auxiliary system. Afterwards, the controller design is carried out in accordance with the adaptive backstepping control method by introduction of the indirect Lyapunov method. To highlight the effectiveness of the proposed control scheme, simulation examples are demonstrated at last. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Thermophysical Properties of Matter - The TPRC Data Series. Volume 3. Thermal Conductivity - Nonmetallic Liquids and Gases

DTIC Science & Technology

1970-01-01

design and experimentation. I. The Shock- Tube Method Smiley [546] introduced the use of shock waves...one of the greatest disadvantages of this technique. Both the unique adaptability of the shock tube method for high -temperature measurement of...Line-Source Flow Method H. The Hot-Wire Thermal Diffusion Column Method I. The Shock- Tube Method J. The Arc Method K. The Ultrasonic Method .

Guideline adaptation and implementation planning: a prospective observational study

PubMed Central

2013-01-01

Background Adaptation of high-quality practice guidelines for local use has been advanced as an efficient means to improve acceptability and applicability of evidence-informed care. In a pan-Canadian study, we examined how cancer care groups adapted pre-existing guidelines to their unique context and began implementation planning. Methods Using a mixed-methods, case-study design, five cases were purposefully sampled from self-identified groups and followed as they used a structured method and resources for guideline adaptation. Cases received the ADAPTE Collaboration toolkit, facilitation, methodological and logistical support, resources and assistance as required. Documentary and primary data collection methods captured individual case experience, including monthly summaries of meeting and field notes, email/telephone correspondence, and project records. Site visits, process audits, interviews, and a final evaluation forum with all cases contributed to a comprehensive account of participant experience. Results Study cases took 12 to >24 months to complete guideline adaptation. Although participants appreciated the structure, most found the ADAPTE method complex and lacking practical aspects. They needed assistance establishing individual guideline mandate and infrastructure, articulating health questions, executing search strategies, appraising evidence, and achieving consensus. Facilitation was described as a multi-faceted process, a team effort, and an essential ingredient for guideline adaptation. While front-line care providers implicitly identified implementation issues during adaptation, they identified a need to add an explicit implementation planning component. Conclusions Guideline adaptation is a positive initial step toward evidence-informed care, but adaptation (vs. ‘de novo’ development) did not meet expectations for reducing time or resource commitments. Undertaking adaptation is as much about the process (engagement and capacity building) as it is about the product (adapted guideline). To adequately address local concerns, cases found it necessary to also search and appraise primary studies, resulting in hybrid (adaptation plus de novo) guideline development strategies that required advanced methodological skills. Adaptation was found to be an action element in the knowledge translation continuum that required integration of an implementation perspective. Accordingly, the adaptation methodology and resources were reformulated and substantially augmented to provide practical assistance to groups not supported by a dedicated guideline panel and to provide more implementation planning support. The resulting framework is called CAN-IMPLEMENT. PMID:23656884

Adaptive design clinical trials: a review of the literature and ClinicalTrials.gov

PubMed Central

Bothwell, Laura E; Avorn, Jerry; Khan, Nazleen F; Kesselheim, Aaron S

2018-01-01

Objectives This review investigates characteristics of implemented adaptive design clinical trials and provides examples of regulatory experience with such trials. Design Review of adaptive design clinical trials in EMBASE, PubMed, Cochrane Registry of Controlled Clinical Trials, Web of Science and ClinicalTrials.gov. Phase I and seamless Phase I/II trials were excluded. Variables extracted from trials included basic study characteristics, adaptive design features, size and use of independent data monitoring committees (DMCs) and blinded interim analyses. We also examined use of the adaptive trials in new drug submissions to the Food and Drug Administration (FDA) and European Medicines Agency (EMA) and recorded regulators’ experiences with adaptive designs. Results 142 studies met inclusion criteria. There has been a recent growth in publicly reported use of adaptive designs among researchers around the world. The most frequently appearing types of adaptations were seamless Phase II/III (57%), group sequential (21%), biomarker adaptive (20%), and adaptive dose-finding designs (16%). About one-third (32%) of trials reported an independent DMC, while 6% reported blinded interim analysis. We found that 9% of adaptive trials were used for FDA product approval consideration, and 12% were used for EMA product approval consideration. International regulators had mixed experiences with adaptive trials. Many product applications with adaptive trials had extensive correspondence between drug sponsors and regulators regarding the adaptive designs, in some cases with regulators requiring revisions or alterations to research designs. Conclusions Wider use of adaptive designs will necessitate new drug application sponsors to engage with regulatory scientists during planning and conduct of the trials. Investigators need to more consistently report protections intended to preserve confidentiality and minimise potential operational bias during interim analysis. PMID:29440155

Truss Optimization for a Manned Nuclear Electric Space Vehicle using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Benford, Andrew; Tinker, Michael L.

2004-01-01

The purpose of this paper is to utilize the genetic algorithm (GA) optimization method for structural design of a nuclear propulsion vehicle. Genetic algorithms provide a guided, random search technique that mirrors biological adaptation. To verify the GA capabilities, other traditional optimization methods were used to generate results for comparison to the GA results, first for simple two-dimensional structures, and then for full-scale three-dimensional truss designs.

Cultural adaptation of a supportive care needs measure for Hispanic men cancer survivors.

PubMed

Martinez Tyson, Dinorah; Medina-Ramirez, Patricia; Vázquez-Otero, Coralia; Gwede, Clement K; Bobonis, Margarita; McMillan, Susan C

2018-01-01

Research with ethnic minority populations requires instrumentation that is cultural and linguistically relevant. The aim of this study was to translate and culturally adapt the Cancer Survivor Unmet Needs measure into Spanish. We describe the iterative, community-engaged consensus-building approaches used to adapt the instrument for Hispanic male cancer survivors. We used an exploratory sequential mixed method study design. Methods included translation and back-translation, focus groups with cancer survivors (n = 18) and providers (n = 5), use of cognitive interview techniques to evaluate the comprehension and acceptability of the adapted instrument with survivors (n = 12), ongoing input from the project's community advisory board, and preliminary psychometric analysis (n = 84). The process emphasized conceptual, content, semantic, and technical equivalence. Combining qualitative and quantitative approaches offered a rigorous, systematic, and contextual approach to translation alone and supports the cultural adaptation of this measure in a purposeful and relevant manner. Our findings highlight the importance of going beyond translation when adapting measures for cross-cultural populations and illustrate the importance of taking culture, literacy, and language into consideration.

Dynamic experiment design regularization approach to adaptive imaging with array radar/SAR sensor systems.

PubMed

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.

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.

An hp-adaptivity and error estimation for hyperbolic conservation laws

NASA Technical Reports Server (NTRS)

Bey, Kim S.

1995-01-01

This paper presents an hp-adaptive discontinuous Galerkin method for linear hyperbolic conservation laws. A priori and a posteriori error estimates are derived in mesh-dependent norms which reflect the dependence of the approximate solution on the element size (h) and the degree (p) of the local polynomial approximation. The a posteriori error estimate, based on the element residual method, provides bounds on the actual global error in the approximate solution. The adaptive strategy is designed to deliver an approximate solution with the specified level of error in three steps. The a posteriori estimate is used to assess the accuracy of a given approximate solution and the a priori estimate is used to predict the mesh refinements and polynomial enrichment needed to deliver the desired solution. Numerical examples demonstrate the reliability of the a posteriori error estimates and the effectiveness of the hp-adaptive strategy.

Turbine blade profile design method based on Bezier curves

NASA Astrophysics Data System (ADS)

Alexeev, R. A.; Tishchenko, V. A.; Gribin, V. G.; Gavrilov, I. Yu.

2017-11-01

In this paper, the technique of two-dimensional parametric blade profile design is presented. Bezier curves are used to create the profile geometry. The main feature of the proposed method is an adaptive approach of curve fitting to given geometric conditions. Calculation of the profile shape is produced by multi-dimensional minimization method with a number of restrictions imposed on the blade geometry.The proposed method has been used to describe parametric geometry of known blade profile. Then the baseline geometry was modified by varying some parameters of the blade. The numerical calculation of obtained designs has been carried out. The results of calculations have shown the efficiency of chosen approach.

Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping

2018-03-01

This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.

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.

Artificial Metamorphosis: Evolutionary Design of Transforming, Soft-Bodied Robots.

PubMed

Joachimczak, Michał; Suzuki, Reiji; Arita, Takaya

2016-01-01

We show how the concept of metamorphosis, together with a biologically inspired model of multicellular development, can be used to evolve soft-bodied robots that are adapted to two very different tasks, such as being able to move in an aquatic and in a terrestrial environment. Each evolved solution defines two pairs of morphologies and controllers, together with a process of transforming one pair into the other. Animats develop from a single cell and grow through cellular divisions and deaths until they reach an initial larval form adapted to a first environment. To obtain the adult form adapted to a second environment, the larva undergoes metamorphosis, during which new cells are added or removed and its controller is modified. Importantly, our approach assumes nothing about what morphologies or methods of locomotion are preferred. Instead, it successfully searches the vast space of possible designs and comes up with complex, surprising, lifelike solutions that are reminiscent of amphibian metamorphosis. We analyze obtained solutions and investigate whether the morphological changes during metamorphosis are indeed adaptive. We then compare the effectiveness of three different types of selective pressures used to evolve metamorphic individuals. Finally, we investigate potential advantages of using metamorphosis to automatically produce soft-bodied designs by comparing the performance of metamorphic individuals with their specialized counterparts and designs that are robust to both environments.

Comparison of Reconstruction and Control algorithms on the ESO end-to-end simulator OCTOPUS

NASA Astrophysics Data System (ADS)

Montilla, I.; Béchet, C.; Lelouarn, M.; Correia, C.; Tallon, M.; Reyes, M.; Thiébaut, É.

Extremely Large Telescopes are very challenging concerning their Adaptive Optics requirements. Their diameters, the specifications demanded by the science for which they are being designed for, and the planned use of Extreme Adaptive Optics systems, imply a huge increment in the number of degrees of freedom in the deformable mirrors. It is necessary to study new reconstruction algorithms to implement the real time control in Adaptive Optics at the required speed. We have studied the performance, applied to the case of the European ELT, of three different algorithms: the matrix-vector multiplication (MVM) algorithm, considered as a reference; the Fractal Iterative Method (FrIM); and the Fourier Transform Reconstructor (FTR). The algorithms have been tested on ESO's OCTOPUS software, which simulates the atmosphere, the deformable mirror, the sensor and the closed-loop control. The MVM is the default reconstruction and control method implemented in OCTOPUS, but it scales in O(N2) operations per loop so it is not considered as a fast algorithm for wave-front reconstruction and control on an Extremely Large Telescope. The two other methods are the fast algorithms studied in the E-ELT Design Study. The performance, as well as their response in the presence of noise and with various atmospheric conditions, has been compared using a Single Conjugate Adaptive Optics configuration for a 42 m diameter ELT, with a total amount of 5402 actuators. Those comparisons made on a common simulator allow to enhance the pros and cons of the various methods, and give us a better understanding of the type of reconstruction algorithm that an ELT demands.

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

PubMed

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

2014-11-01

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

Classification of adaptive memetic algorithms: a comparative study.

PubMed

Ong, Yew-Soon; Lim, Meng-Hiot; Zhu, Ning; Wong, Kok-Wai

2006-02-01

Adaptation of parameters and operators represents one of the recent most important and promising areas of research in evolutionary computations; it is a form of designing self-configuring algorithms that acclimatize to suit the problem in hand. Here, our interests are on a recent breed of hybrid evolutionary algorithms typically known as adaptive memetic algorithms (MAs). One unique feature of adaptive MAs is the choice of local search methods or memes and recent studies have shown that this choice significantly affects the performances of problem searches. In this paper, we present a classification of memes adaptation in adaptive MAs on the basis of the mechanism used and the level of historical knowledge on the memes employed. Then the asymptotic convergence properties of the adaptive MAs considered are analyzed according to the classification. Subsequently, empirical studies on representatives of adaptive MAs for different type-level meme adaptations using continuous benchmark problems indicate that global-level adaptive MAs exhibit better search performances. Finally we conclude with some promising research directions in the area.

Joint-space adaptive control of a 6 DOF end-effector with closed-kinematic chain mechanism

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Zhou, Zhen-Lei

1989-01-01

The development is presented for a joint-space adaptive scheme that controls the joint position of a six-degree-of-freedom (DOF) robot end-effector performing fine and precise motion within a very limited workspace. The end-effector was built to study autonomous assembly of NASA hardware in space. The design of the adaptive controller is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method. In the development, it is assumed that the end-effector performs slowly varying motion. Computer simulation is performed to investigate the performance of the developed control scheme on position control of the end-effector. Simulation results manifest that the adaptive control scheme provides excellent tracking of several test paths.

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies.

PubMed

Duffull, Stephen B; Graham, Gordon; Mengersen, Kerrie; Eccleston, John

2012-01-01

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.

Policy tree optimization for adaptive management of water resources systems

NASA Astrophysics Data System (ADS)

Herman, Jonathan; Giuliani, Matteo

2017-04-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points" that suggest the need of updating the policy. However, there remains a need for a general method to optimize the choice of the signposts to be used and their threshold values. This work contributes a general framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. Given a set of feature variables (e.g., reservoir level, inflow observations, inflow forecasts), the resulting policy defines both the optimal reservoir operations and the conditions under which such operations should be triggered. We demonstrate the approach using Folsom Reservoir (California) as a case study, in which operating policies must balance the risk of both floods and droughts. Numerical results show that the tree-based policies outperform the ones designed via Dynamic Programming. In addition, they display good adaptive capacity to the changing climate, successfully adapting the reservoir operations across a large set of uncertain climate scenarios.

Andragogical Methods to Sustain Quality Adult Education in Ethiopia

ERIC Educational Resources Information Center

Seyoum, Yilfashewa; Basha, Garkebo

2017-01-01

This study aims to analyse the extent andragogy serves as a means to secure quality in adult education programs. It attempts to scrutinize how active learning methods are implemented effectively in adult education program in the Eastern part of Ethiopia. A survey research design was adapted as a method of the study. Stratified and purposive…

The Contextualized Technology Adaptation Process (CTAP): Optimizing Health Information Technology to Improve Mental Health Systems.

PubMed

Lyon, Aaron R; Wasse, Jessica Knaster; Ludwig, Kristy; Zachry, Mark; Bruns, Eric J; Unützer, Jürgen; McCauley, Elizabeth

2016-05-01

Health information technologies have become a central fixture in the mental healthcare landscape, but few frameworks exist to guide their adaptation to novel settings. This paper introduces the contextualized technology adaptation process (CTAP) and presents data collected during Phase 1 of its application to measurement feedback system development in school mental health. The CTAP is built on models of human-centered design and implementation science and incorporates repeated mixed methods assessments to guide the design of technologies to ensure high compatibility with a destination setting. CTAP phases include: (1) Contextual evaluation, (2) Evaluation of the unadapted technology, (3) Trialing and evaluation of the adapted technology, (4) Refinement and larger-scale implementation, and (5) Sustainment through ongoing evaluation and system revision. Qualitative findings from school-based practitioner focus groups are presented, which provided information for CTAP Phase 1, contextual evaluation, surrounding education sector clinicians' workflows, types of technologies currently available, and influences on technology use. Discussion focuses on how findings will inform subsequent CTAP phases, as well as their implications for future technology adaptation across content domains and service sectors.

Consumer Mathematics. Teacher's Guide [and Student Guide]. Parallel Alternative Strategies for Students (PASS).

ERIC Educational Resources Information Center

Walford, Sylvia B.; Thomas, Portia R.

This teacher's guide and student guide are designed to accompany a consumer mathematics textbook that contains supplemental readings, activities, and methods adapted for secondary students who have disabilities and other students with diverse learning needs. The materials are designed to help these students succeed in regular education content…

Topology optimization of induction heating model using sequential linear programming based on move limit with adaptive relaxation

NASA Astrophysics Data System (ADS)

Masuda, Hiroshi; Kanda, Yutaro; Okamoto, Yoshifumi; Hirono, Kazuki; Hoshino, Reona; Wakao, Shinji; Tsuburaya, Tomonori

2017-12-01

It is very important to design electrical machineries with high efficiency from the point of view of saving energy. Therefore, topology optimization (TO) is occasionally used as a design method for improving the performance of electrical machinery under the reasonable constraints. Because TO can achieve a design with much higher degree of freedom in terms of structure, there is a possibility for deriving the novel structure which would be quite different from the conventional structure. In this paper, topology optimization using sequential linear programming using move limit based on adaptive relaxation is applied to two models. The magnetic shielding, in which there are many local minima, is firstly employed as firstly benchmarking for the performance evaluation among several mathematical programming methods. Secondly, induction heating model is defined in 2-D axisymmetric field. In this model, the magnetic energy stored in the magnetic body is maximized under the constraint on the volume of magnetic body. Furthermore, the influence of the location of the design domain on the solutions is investigated.

GLOBECOM '86 - Global Telecommunications Conference, Houston, TX, Dec. 1-4, 1986, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Papers are presented on local area networks; formal methods for communication protocols; computer simulation of communication systems; spread spectrum and coded communications; tropical radio propagation; VLSI for communications; strategies for increasing software productivity; multiple access communications; advanced communication satellite technologies; and spread spectrum systems. Topics discussed include Space Station communication and tracking development and design; transmission networks; modulation; data communications; computer network protocols and performance; and coding and synchronization. Consideration is given to free space optical communications systems; VSAT communication networks; network topology design; advances in adaptive filtering echo cancellation and adaptive equalization; advanced signal processing for satellite communications; the elements, design, and analysis of fiber-optic networks; and advances in digital microwave systems.

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.; Schumann, Johann; Guenther, Kurt; Bosworth, John

2006-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

Anthropology and International Business Research Methods in DBA Teaching: Frameworks for Cultural Awareness.

ERIC Educational Resources Information Center

Whiteley, Alma

2001-01-01

Discusses the rationale for introducing anthropology into a doctoral-level international business research methods course. Describes three anthropological frameworks designed for the course: a cultural awareness model adapted from G. Morgan's (1980) idea of paradigmatic orthodoxy; key organizing principles; and a mapping model allowing researchers…

An ACC Design Method for Achieving Both String Stability and Ride Comfort

NASA Astrophysics Data System (ADS)

Yamamura, Yoshinori; Seto, Yoji; Nishira, Hikaru; Kawabe, Taketoshi

An investigation was made of a method for designing adaptive cruise control (ACC) so as to achieve a headway distance response that feels natural to the driver while at the same time obtaining high levels of both string stability and ride comfort. With this design method, the H∞ norm is adopted as the index of string stability. Additionally, two norms are introduced for evaluating ride comfort and natural vehicle behavior. The relationship between these three norms and headway distance response characteristics was analyzed, and an evaluation method was established for achieving high levels of the various performance characteristics required of ACC. An ACC system designed with this method was evaluated in driving tests conducted on a proving ground course, and the results confirmed that it achieved the targeted levels of string stability, ride comfort and natural vehicle behavior.

Structural optimization: Status and promise

NASA Astrophysics Data System (ADS)

Kamat, Manohar P.

Chapters contained in this book include fundamental concepts of optimum design, mathematical programming methods for constrained optimization, function approximations, approximate reanalysis methods, dual mathematical programming methods for constrained optimization, a generalized optimality criteria method, and a tutorial and survey of multicriteria optimization in engineering. Also included are chapters on the compromise decision support problem and the adaptive linear programming algorithm, sensitivity analyses of discrete and distributed systems, the design sensitivity analysis of nonlinear structures, optimization by decomposition, mixed elements in shape sensitivity analysis of structures based on local criteria, and optimization of stiffened cylindrical shells subjected to destabilizing loads. Other chapters are on applications to fixed-wing aircraft and spacecraft, integrated optimum structural and control design, modeling concurrency in the design of composite structures, and tools for structural optimization. (No individual items are abstracted in this volume)

A practical globalization of one-shot optimization for optimal design of tokamak divertors

NASA Astrophysics Data System (ADS)

Blommaert, Maarten; Dekeyser, Wouter; Baelmans, Martine; Gauger, Nicolas R.; Reiter, Detlev

2017-01-01

In past studies, nested optimization methods were successfully applied to design of the magnetic divertor configuration in nuclear fusion reactors. In this paper, so-called one-shot optimization methods are pursued. Due to convergence issues, a globalization strategy for the one-shot solver is sought. Whereas Griewank introduced a globalization strategy using a doubly augmented Lagrangian function that includes primal and adjoint residuals, its practical usability is limited by the necessity of second order derivatives and expensive line search iterations. In this paper, a practical alternative is offered that avoids these drawbacks by using a regular augmented Lagrangian merit function that penalizes only state residuals. Additionally, robust rank-two Hessian estimation is achieved by adaptation of Powell's damped BFGS update rule. The application of the novel one-shot approach to magnetic divertor design is considered in detail. For this purpose, the approach is adapted to be complementary with practical in parts adjoint sensitivities. Using the globalization strategy, stable convergence of the one-shot approach is achieved.

Adapting iterative algorithms for solving large sparse linear systems for efficient use on the CDC CYBER 205

NASA Technical Reports Server (NTRS)

Kincaid, D. R.; Young, D. M.

1984-01-01

Adapting and designing mathematical software to achieve optimum performance on the CYBER 205 is discussed. Comments and observations are made in light of recent work done on modifying the ITPACK software package and on writing new software for vector supercomputers. The goal was to develop very efficient vector algorithms and software for solving large sparse linear systems using iterative methods.

Designs and adaptive analysis plans for pivotal clinical trials of therapeutics and companion diagnostics.

PubMed

Simon, Richard

2008-06-01

Developments in genomics and biotechnology provide unprecedented opportunities for the development of effective therapeutics and companion diagnostics for matching the right drug to the right patient. Effective co-development involves many new challenges with increased opportunity for success as well as delay and failure. Clinical trial designs and adaptive analysis plans for the prospective design of pivotal trials of new therapeutics and companion diagnostics are reviewed. Effective co-development requires careful prospective planning of the design and analysis strategy for pivotal clinical trials. Randomized clinical trials continue to be important for evaluating the effectiveness of new treatments, but the target populations for analysis should be prospectively specified based on the companion diagnostic. Post hoc analyses of traditionally designed randomized clinical trials are often deeply problematic. Clear separation is generally required of the data used for developing the diagnostic test, including their threshold of positivity, from the data used for evaluating treatment effectiveness in subsets determined by the test. Adaptive analysis can be used to provide flexibility to the analysis but the use of such methods requires careful planning and prospective definition in order to assure that the pivotal trial adequately limits the chance of erroneous conclusions.

Expanded envelope concepts for aircraft control-element failure detection and identification

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1988-01-01

The purpose of this effort was to develop and demonstrate concepts for expanding the envelope of failure detection and isolation (FDI) algorithms for aircraft-path failures. An algorithm which uses analytic-redundancy in the form of aerodynamic force and moment balance equations was used. Because aircraft-path FDI uses analytical models, there is a tradeoff between accuracy and the ability to detect and isolate failures. For single flight condition operation, design and analysis methods are developed to deal with this robustness problem. When the departure from the single flight condition is significant, algorithm adaptation is necessary. Adaptation requirements for the residual generation portion of the FDI algorithm are interpreted as the need for accurate, large-motion aero-models, over a broad range of velocity and altitude conditions. For the decision-making part of the algorithm, adaptation may require modifications to filtering operations, thresholds, and projection vectors that define the various hypothesis tests performed in the decision mechanism. Methods of obtaining and evaluating adequate residual generation and decision-making designs have been developed. The application of the residual generation ideas to a high-performance fighter is demonstrated by developing adaptive residuals for the AFTI-F-16 and simulating their behavior under a variety of maneuvers using the results of a NASA F-16 simulation.

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

NASA Astrophysics Data System (ADS)

Leitao, Paulo

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

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

Automated Design of Quantum Circuits

NASA Technical Reports Server (NTRS)

Williams, Colin P.; Gray, Alexander G.

2000-01-01

In order to design a quantum circuit that performs a desired quantum computation, it is necessary to find a decomposition of the unitary matrix that represents that computation in terms of a sequence of quantum gate operations. To date, such designs have either been found by hand or by exhaustive enumeration of all possible circuit topologies. In this paper we propose an automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem. We demonstrate the method on the task of discovering quantum circuit designs for quantum teleportation. We show that to find a given known circuit design (one which was hand-crafted by a human), the method considers roughly an order of magnitude fewer designs than naive enumeration. In addition, the method finds novel circuit designs superior to those previously known.

No More Green Thumbs!

ERIC Educational Resources Information Center

Bland, Judith A.

1977-01-01

An alternative method of bacterial spore staining using malachite green is described. This technique is designed to save time and expense by a less messy procedure. Advantages and adaptations of the technique are also given. (MR)

MRAC Revisited: Guaranteed Performance with Reference Model Modification

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmaje

2010-01-01

This paper presents modification of the conventional model reference adaptive control (MRAC) architecture in order to achieve guaranteed transient performance both in the output and input signals of an uncertain system. The proposed modification is based on the tracking error feedback to the reference model. It is shown that approach guarantees tracking of a given command and the ideal control signal (one that would be designed if the system were known) not only asymptotically but also in transient by a proper selection of the error feedback gain. The method prevents generation of high frequency oscillations that are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference command of any magnitude form any initial position without re-tuning. The benefits of the method are demonstrated in simulations.

Parameter Studies, time-dependent simulations and design with automated Cartesian methods

NASA Technical Reports Server (NTRS)

Aftosmis, Michael

2005-01-01

Over the past decade, NASA has made a substantial investment in developing adaptive Cartesian grid methods for aerodynamic simulation. Cartesian-based methods played a key role in both the Space Shuttle Accident Investigation and in NASA's return to flight activities. The talk will provide an overview of recent technological developments focusing on the generation of large-scale aerodynamic databases, automated CAD-based design, and time-dependent simulations with of bodies in relative motion. Automation, scalability and robustness underly all of these applications and research in each of these topics will be presented.

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Paradigms for adaptive statistical information designs: practical experiences and strategies.

PubMed

Wang, Sue-Jane; Hung, H M James; O'Neill, Robert

2012-11-10

In the last decade or so, interest in adaptive design clinical trials has gradually been directed towards their use in regulatory submissions by pharmaceutical drug sponsors to evaluate investigational new drugs. Methodological advances of adaptive designs are abundant in the statistical literature since the 1970s. The adaptive design paradigm has been enthusiastically perceived to increase the efficiency and to be more cost-effective than the fixed design paradigm for drug development. Much interest in adaptive designs is in those studies with two-stages, where stage 1 is exploratory and stage 2 depends upon stage 1 results, but where the data of both stages will be combined to yield statistical evidence for use as that of a pivotal registration trial. It was not until the recent release of the US Food and Drug Administration Draft Guidance for Industry on Adaptive Design Clinical Trials for Drugs and Biologics (2010) that the boundaries of flexibility for adaptive designs were specifically considered for regulatory purposes, including what are exploratory goals, and what are the goals of adequate and well-controlled (A&WC) trials (2002). The guidance carefully described these distinctions in an attempt to minimize the confusion between the goals of preliminary learning phases of drug development, which are inherently substantially uncertain, and the definitive inference-based phases of drug development. In this paper, in addition to discussing some aspects of adaptive designs in a confirmatory study setting, we underscore the value of adaptive designs when used in exploratory trials to improve planning of subsequent A&WC trials. One type of adaptation that is receiving attention is the re-estimation of the sample size during the course of the trial. We refer to this type of adaptation as an adaptive statistical information design. Specifically, a case example is used to illustrate how challenging it is to plan a confirmatory adaptive statistical information design. We highlight the substantial risk of planning the sample size for confirmatory trials when information is very uninformative and stipulate the advantages of adaptive statistical information designs for planning exploratory trials. Practical experiences and strategies as lessons learned from more recent adaptive design proposals will be discussed to pinpoint the improved utilities of adaptive design clinical trials and their potential to increase the chance of a successful drug development. Published 2012. This article is a US Government work and is in the public domain in the USA.

Cultural Adaptations of Behavioral Health Interventions: A Progress Report

PubMed Central

Barrera, Manuel

2014-01-01

Objective To reduce health disparities, behavioral health interventions must reach subcultural groups and demonstrate effectiveness in improving their health behaviors and outcomes. One approach to developing such health interventions is to culturally adapt original evidence-based interventions. The goals of the paper are to (a) describe consensus on the stages involved in developing cultural adaptations, (b) identify common elements in cultural adaptations, (c) examine evidence on the effectiveness of culturally enhanced interventions for various health conditions, and (d) pose questions for future research. Method Influential literature from the past decade was examined to identify points of consensus. Results There is agreement that cultural adaptation can be organized into five stages: information gathering, preliminary design, preliminary testing, refinement, and final trial. With few exceptions, reviews of several health conditions (e.g., AIDS, asthma, diabetes) concluded that culturally enhanced interventions are more effective in improving health outcomes than usual care or other control conditions. Conclusion Progress has been made in establishing methods for conducting cultural adaptations and providing evidence of their effectiveness. Future research should include evaluations of cultural adaptations developed in stages, tests to determine the effectiveness of cultural adaptations relative to the original versions, and studies that advance our understanding of cultural constructs’ contributions to intervention engagement and efficacy. PMID:22289132

Climate Change Impacts and Vulnerability Assessment in Industrial Complexes

NASA Astrophysics Data System (ADS)

Lee, H. J.; Lee, D. K.

2016-12-01

Climate change has recently caused frequent natural disasters, such as floods, droughts, and heat waves. Such disasters have also increased industrial damages. We must establish climate change adaptation policies to reduce the industrial damages. It is important to make accurate vulnerability assessment to establish climate change adaptation policies. Thus, this study aims at establishing a new index to assess vulnerability level in industrial complexes. Most vulnerability indices have been developed with subjective approaches, such as the Delphi survey and the Analytic Hierarchy Process(AHP). The subjective approaches rely on the knowledge of a few experts, which provokes the lack of the reliability of the indices. To alleviate the problem, we have designed a vulnerability index incorporating objective approaches. We have investigated 42 industrial complex sites in Republic of Korea (ROK). To calculate weights of variables, we used entropy method as an objective method integrating the Delphi survey as a subjective method. Finally, we found our method integrating both subjective method and objective method could generate result. The integration of the entropy method enables us to assess the vulnerability objectively. Our method will be useful to establish climate change adaptation policies by reducing the uncertainties of the methods based on the subjective approaches.

Design and Development of an Equipotential Voltage Reference (Grounding) System for a Low-Cost Rapid-Development Modular Spacecraft Architecture

NASA Technical Reports Server (NTRS)

Lukash, James A.; Daley, Earl

2011-01-01

This work describes the design and development effort to adapt rapid-development space hardware by creating a ground system using solutions of low complexity, mass, & cost. The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft is based on the modular common spacecraft bus architecture developed at NASA Ames Research Center. The challenge was building upon the existing modular common bus design and development work and improving the LADEE spacecraft design by adding an Equipotential Voltage Reference (EVeR) system, commonly referred to as a ground system. This would aid LADEE in meeting Electromagnetic Environmental Effects (E3) requirements, thereby making the spacecraft more compatible with itself and its space environment. The methods used to adapt existing hardware are presented, including provisions which may be used on future spacecraft.

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

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

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

Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

New head gradient coil design and construction techniques

PubMed Central

Handler, William B; Harris, Chad T; Scholl, Timothy J; Parker, Dennis L; Goodrich, K Craig; Dalrymple, Brian; Van Sass, Frank; Chronik, Blaine A

2013-01-01

Purpose To design and build a head insert gradient coil to use in conjunction with body gradients for superior imaging. Materials and Methods The use of the Boundary Element Method to solve for a gradient coil wire pattern on an arbitrary surface has allowed us to incorporate engineering changes into the electromagnetic design of a gradient coil directly. Improved wire pattern design has been combined with robust manufacturing techniques and novel cooling methods. Results The finished coil had an efficiency of 0.15 mT/m/A in all three axes and allowed the imaging region to extend across the entire head and upper part of the neck. Conclusion The ability to adapt your electromagnetic design to necessary changes from an engineering perspective leads to superior coil performance. PMID:24123485

Radiofrequency pulse design using nonlinear gradient magnetic fields.

PubMed

Kopanoglu, Emre; Constable, R Todd

2015-09-01

An iterative k-space trajectory and radiofrequency (RF) pulse design method is proposed for excitation using nonlinear gradient magnetic fields. The spatial encoding functions (SEFs) generated by nonlinear gradient fields are linearly dependent in Cartesian coordinates. Left uncorrected, this may lead to flip angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a matching pursuit algorithm, and the RF pulse is designed using a conjugate gradient algorithm. Three variants of the proposed approach are given: the full algorithm, a computationally cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. The method is compared with other iterative (matching pursuit and conjugate gradient) and noniterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity. An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. © 2014 Wiley Periodicals, Inc.

Probe-Directed Degradation (PDD) for Flexible Removal of Unwanted cDNA Sequences from RNA-Seq Libraries.

PubMed

Archer, Stuart K; Shirokikh, Nikolay E; Preiss, Thomas

2015-04-01

Most applications for RNA-seq require the depletion of abundant transcripts to gain greater coverage of the underlying transcriptome. The sequences to be targeted for depletion depend on application and species and in many cases may not be supported by commercial depletion kits. This unit describes a method for generating RNA-seq libraries that incorporates probe-directed degradation (PDD), which can deplete any unwanted sequence set, with the low-bias split-adapter method of library generation (although many other library generation methods are in principle compatible). The overall strategy is suitable for applications requiring customized sequence depletion or where faithful representation of fragment ends and lack of sequence bias is paramount. We provide guidelines to rapidly design specific probes against the target sequence, and a detailed protocol for library generation using the split-adapter method including several strategies for streamlining the technique and reducing adapter dimer content. Copyright © 2015 John Wiley & Sons, Inc.

Algebraic and adaptive learning in neural control systems

NASA Astrophysics Data System (ADS)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of the failure constraints in the deterministic and reliability based optimization of the ITPS panel. It was shown that using adaptive sampling, the number of designs required to find the optimum were reduced drastically, while improving the accuracy. System reliability of ITPS was estimated using Monte Carlo Simulation (MCS) based method. Separable Monte Carlo method was employed that allowed separable sampling of the random variables to predict the probability of failure accurately. The reliability analysis considered uncertainties in the geometry, material properties, loading conditions of the panel and error in finite element modeling. These uncertainties further increased the computational cost of MCS techniques which was also reduced by employing surrogate models. In order to estimate the error in the probability of failure estimate, bootstrapping method was applied. This research work thus demonstrates optimization of the ITPS composite panel with multiple failure modes and large number of uncertainties using adaptive sampling techniques.

Adapting School-Based Substance Use Prevention Curriculum Through Cultural Grounding: A Review and Exemplar of Adaptation Processes for Rural Schools

PubMed Central

Colby, Margaret; Hecht, Michael L.; Miller-Day, Michelle; Krieger, Janice L.; Syvertsen, Amy K.; Graham, John W.; Pettigrew, Jonathan

2014-01-01

A central challenge facing twenty-first century community-based researchers and prevention scientists is curriculum adaptation processes. While early prevention efforts sought to develop effective programs, taking programs to scale implies that they will be adapted, especially as programs are implemented with populations other than those with whom they were developed or tested. The principle of cultural grounding, which argues that health message adaptation should be informed by knowledge of the target population and by cultural insiders, provides a theoretical rational for cultural regrounding and presents an illustrative case of methods used to reground the keepin’ it REAL substance use prevention curriculum for a rural adolescent population. We argue that adaptation processes like those presented should be incorporated into the design and dissemination of prevention interventions. PMID:22961604

Adapting school-based substance use prevention curriculum through cultural grounding: a review and exemplar of adaptation processes for rural schools.

PubMed

Colby, Margaret; Hecht, Michael L; Miller-Day, Michelle; Krieger, Janice L; Syvertsen, Amy K; Graham, John W; Pettigrew, Jonathan

2013-03-01

A central challenge facing twenty-first century community-based researchers and prevention scientists is curriculum adaptation processes. While early prevention efforts sought to develop effective programs, taking programs to scale implies that they will be adapted, especially as programs are implemented with populations other than those with whom they were developed or tested. The principle of cultural grounding, which argues that health message adaptation should be informed by knowledge of the target population and by cultural insiders, provides a theoretical rational for cultural regrounding and presents an illustrative case of methods used to reground the keepin' it REAL substance use prevention curriculum for a rural adolescent population. We argue that adaptation processes like those presented should be incorporated into the design and dissemination of prevention interventions.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Usability evaluation of intradermal adapters (IDA).

PubMed

Tsals, Izrail

2017-03-27

Intradermal adapter device technology minimizes the complexity of the Mantoux technique, thereby providing predictable, reproducible intradermal (ID) injections and removing the concerns regarding the ease and reliability of Mantoux technique when using conventional needle and syringe. The technology employs a simple device with geometry designed to gently deform the skin surface and the subcutaneous tissue, providing the ideal angle and depth of needle insertion for consistently successful intradermal injections. The results of this development were presented at the First, Second and Third Skin Vaccination Summits in 2011, 2013 and 2015 respectively [1,2,3]. The current publication addresses the performance of intradermal adapters (IDA) evaluated in three preclinical studies. The evaluations were based on the assessment of bleb formation in a skin model, an accepted indicator of ID injection success. All evaluated devices share the same proprietary dermal interface technology. Devices instituting this design are easy to use, require minimal training, and employ conventionally molded parts and cannula. These studies evaluated IDAs of initial design integral with luer lock needles, IDAs for use with conventional syringes, and intradermal adapters for use with auto disable syringes (ADID adapters). The evaluated ID adapters were intended to consistently place the lancet of the needle at a depth of 0.75mm from the skin's surface. This placement depth addresses the variation in the skin thickness at immunization sites for the majority of patients independent of many other variables. Most participants preferred the intradermal adapter method over the traditional Mantoux and identified a need for the adapter at their workplace. Evaluation of IDAs by registered nurses indicated these devices increase success of bleb formation. The use of IDA increased the success of forming blebs by about 30%. Nurses felt the injections were much easier to perform, in particular by novices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive trial designs: a review of barriers and opportunities

PubMed Central

2012-01-01

Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice. PMID:22917111

Online learning control using adaptive critic designs with sparse kernel machines.

PubMed

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Adaptive Formation Control of Electrically Driven Nonholonomic Mobile Robots With Limited Information.

PubMed

Bong Seok Park; Jin Bae Park; Yoon Ho Choi

2011-08-01

We present a leader-follower-based adaptive formation control method for electrically driven nonholonomic mobile robots with limited information. First, an adaptive observer is developed under the condition that the velocity measurement is not available. With the proposed adaptive observer, the formation control part is designed to achieve the desired formation and guarantee the collision avoidance. In addition, neural network is employed to compensate the actuator saturation, and the projection algorithm is used to estimate the velocity information of the leader. It is shown, by using the Lyapunov theory, that all errors of the closed-loop system are uniformly ultimately bounded. Simulation results are presented to illustrate the performance of the proposed control system.

Can emergency medicine research benefit from adaptive design clinical trials?

PubMed

Flight, Laura; Julious, Steven A; Goodacre, Steve

2017-04-01

Adaptive design clinical trials use preplanned interim analyses to determine whether studies should be stopped or modified before recruitment is complete. Emergency medicine trials are well suited to these designs as many have a short time to primary outcome relative to the length of recruitment. We hypothesised that the majority of published emergency medicine trials have the potential to use a simple adaptive trial design. We reviewed clinical trials published in three emergency medicine journals between January 2003 and December 2013. We determined the proportion that used an adaptive design as well as the proportion that could have used a simple adaptive design based on the time to primary outcome and length of recruitment. Only 19 of 188 trials included in the review were considered to have used an adaptive trial design. A total of 154/165 trials that were fixed in design had the potential to use an adaptive design. Currently, there seems to be limited uptake in the use of adaptive trial designs in emergency medicine despite their potential benefits to save time and resources. Failing to take advantage of adaptive designs could be costly to patients and research. It is recommended that where practical and logistical considerations allow, adaptive designs should be used for all emergency medicine clinical trials. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Adapting the Wii Fit Balance Board to Enable Active Video Game Play by Wheelchair Users: User-Centered Design and Usability Evaluation

PubMed Central

Kirkland, William B; Misko, Samuel R; Padalabalanarayanan, Sangeetha; Malone, Laurie A

2018-01-01

Background Active video game (AVG) playing, also known as “exergaming,” is increasingly employed to promote physical activity across all age groups. The Wii Fit Balance Board is a popular gaming controller for AVGs and is used in a variety of settings. However, the commercial off-the-shelf (OTS) design poses several limitations. It is inaccessible to wheelchair users, does not support the use of stabilization assistive devices, and requires the ability to shift the center of balance (COB) in all directions to fully engage in game play. Objective The aim of this study was to design an adapted version of the Wii Fit Balance Board to overcome the identified limitations and to evaluate the usability of the newly designed adapted Wii Fit Balance Board in persons with mobility impairments. Methods In a previous study, 16 participants tried the OTS version of the Wii Fit Balance Board. On the basis of observed limitations, a team of engineers developed and adapted the design of the Wii Fit Balance Board, which was then subjected to multiple iterations of user feedback and design tweaks. On design completion, we recruited a new pool of participants with mobility impairments for a larger study. During their first visit, we assessed lower-extremity function using selected mobility tasks from the International Classification of Functioning, Disability and Health. During a subsequent session, participants played 2 sets of games on both the OTS and adapted versions of the Wii Fit Balance Board. Order of controller version played first was randomized. After participants played each version, we administered the System Usability Scale (SUS) to examine the participants’ perceived usability. Results The adapted version of the Wii Fit Balance Board resulting from the user-centered design approach met the needs of a variety of users. The adapted controller (1) allowed manual wheelchair users to engage in game play, which was previously not possible; (2) included Americans with Disabilities Act-compliant handrails as part of the controller, enabling stable and safe game play; and (3) included a sensitivity control feature, allowing users to fine-tune the controller to match the users’ range of COB motion. More than half the sample could not use the OTS version of the Wii Fit Balance Board, while all participants were able to use the adapted version. All participants rated the adapted Wii Fit Balance Board at a minimum as “good,” while those who could not use the OTS Wii Fit Balance Board rated the adapted Wii Fit Balance Board as “excellent.” We found a significant negative correlation between lower-extremity function and differences between OTS and adapted SUS scores, indicating that as lower-extremity function decreased, participants perceived the adapted Wii Fit Balance Board as more usable. Conclusions This study demonstrated a successful adaptation of a widely used AVG controller. The adapted controller’s potential to increase physical activity levels among people with mobility impairments will be evaluated in a subsequent trial. Trial Registration ClinicalTrials.gov NCT02994199; https://clinicaltrials.gov/ct2/show/NCT02994199 (Archived by WebCite at http://www.webcitation.org/6xWTyiJWf) PMID:29510972

Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach.

PubMed

Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian

2011-04-01

This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

Effect of an Adapted "Cover Write" Method to Word-Naming and Spelling to Students with Developmental Disabilities in Turkey

ERIC Educational Resources Information Center

Erbas, Dilek; Turan, Yasemin; Ozen, Arzu; Halle, James W.

2006-01-01

The purpose of the present study was to assess the effectiveness of the "cover write" method of teaching word-naming and spelling to two Turkish students with developmental disabilities. A multiple-probe design across three, 5-word sets was employed to assess the effectiveness of the intervention. The "cover write" method was…

Comparison of adaptive critic-based and classical wide-area controllers for power systems.

PubMed

Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

2008-08-01

An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

An adaptable binary entropy coder

NASA Technical Reports Server (NTRS)

Kiely, A.; Klimesh, M.

2001-01-01

We present a novel entropy coding technique which is based on recursive interleaving of variable-to-variable length binary source codes. We discuss code design and performance estimation methods, as well as practical encoding and decoding algorithms.

Spectrum analysis on quality requirements consideration in software design documents.

PubMed

Kaiya, Haruhiko; Umemura, Masahiro; Ogata, Shinpei; Kaijiri, Kenji

2013-12-01

Software quality requirements defined in the requirements analysis stage should be implemented in the final products, such as source codes and system deployment. To guarantee this meta-requirement, quality requirements should be considered in the intermediate stages, such as the design stage or the architectural definition stage. We propose a novel method for checking whether quality requirements are considered in the design stage. In this method, a technique called "spectrum analysis for quality requirements" is applied not only to requirements specifications but also to design documents. The technique enables us to derive the spectrum of a document, and quality requirements considerations in the document are numerically represented in the spectrum. We can thus objectively identify whether the considerations of quality requirements in a requirements document are adapted to its design document. To validate the method, we applied it to commercial software systems with the help of a supporting tool, and we confirmed that the method worked well.

Specification and Design Methodologies for High-Speed Fault-Tolerant Array Algorithms and Structures for VLSI.

DTIC Science & Technology

1987-06-01

evaluation and chip layout planning for VLSI digital systems. A high-level applicative (functional) language, implemented at UCLA, allows combining of...operating system. 2.1 Introduction The complexity of VLSI requires the application of CAD tools at all levels of the design process. In order to be...effective, these tools must be adaptive to the specific design. In this project we studied a design method based on the use of applicative languages

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.

Interactive design optimization of magnetorheological-brake actuators using the Taguchi method

NASA Astrophysics Data System (ADS)

Erol, Ozan; Gurocak, Hakan

2011-10-01

This research explored an optimization method that would automate the process of designing a magnetorheological (MR)-brake but still keep the designer in the loop. MR-brakes apply resistive torque by increasing the viscosity of an MR fluid inside the brake. This electronically controllable brake can provide a very large torque-to-volume ratio, which is very desirable for an actuator. However, the design process is quite complex and time consuming due to many parameters. In this paper, we adapted the popular Taguchi method, widely used in manufacturing, to the problem of designing a complex MR-brake. Unlike other existing methods, this approach can automatically identify the dominant parameters of the design, which reduces the search space and the time it takes to find the best possible design. While automating the search for a solution, it also lets the designer see the dominant parameters and make choices to investigate only their interactions with the design output. The new method was applied for re-designing MR-brakes. It reduced the design time from a week or two down to a few minutes. Also, usability experiments indicated significantly better brake designs by novice users.

Adaptive tracking control for a class of stochastic switched systems

NASA Astrophysics Data System (ADS)

Zhang, Hui; Xia, Yuanqing

2018-02-01

The problem of adaptive tracking is considered for a class of stochastic switched systems, in this paper. As preliminaries, the criterion of global asymptotical practical stability in probability is first presented by the aid of common Lyapunov function method. Based on the Lyapunov stability criterion, adaptive backstepping controllers are designed to guarantee that the closed-loop system has a unique global solution, which is globally asymptotically practically stable in probability, and the tracking error in the fourth moment converges to an arbitrarily small neighbourhood of zero. Simulation examples are given to demonstrate the efficiency of the proposed schemes.

Estimated spectrum adaptive postfilter and the iterative prepost filtering algirighms

NASA Technical Reports Server (NTRS)

Linares, Irving (Inventor)

2004-01-01

The invention presents The Estimated Spectrum Adaptive Postfilter (ESAP) and the Iterative Prepost Filter (IPF) algorithms. These algorithms model a number of image-adaptive post-filtering and pre-post filtering methods. They are designed to minimize Discrete Cosine Transform (DCT) blocking distortion caused when images are highly compressed with the Joint Photographic Expert Group (JPEG) standard. The ESAP and the IPF techniques of the present invention minimize the mean square error (MSE) to improve the objective and subjective quality of low-bit-rate JPEG gray-scale images while simultaneously enhancing perceptual visual quality with respect to baseline JPEG images.

Adaptive Mesh Refinement for Microelectronic Device Design

NASA Technical Reports Server (NTRS)

Cwik, Tom; Lou, John; Norton, Charles

1999-01-01

Finite element and finite volume methods are used in a variety of design simulations when it is necessary to compute fields throughout regions that contain varying materials or geometry. Convergence of the simulation can be assessed by uniformly increasing the mesh density until an observable quantity stabilizes. Depending on the electrical size of the problem, uniform refinement of the mesh may be computationally infeasible due to memory limitations. Similarly, depending on the geometric complexity of the object being modeled, uniform refinement can be inefficient since regions that do not need refinement add to the computational expense. In either case, convergence to the correct (measured) solution is not guaranteed. Adaptive mesh refinement methods attempt to selectively refine the region of the mesh that is estimated to contain proportionally higher solution errors. The refinement may be obtained by decreasing the element size (h-refinement), by increasing the order of the element (p-refinement) or by a combination of the two (h-p refinement). A successful adaptive strategy refines the mesh to produce an accurate solution measured against the correct fields without undue computational expense. This is accomplished by the use of a) reliable a posteriori error estimates, b) hierarchal elements, and c) automatic adaptive mesh generation. Adaptive methods are also useful when problems with multi-scale field variations are encountered. These occur in active electronic devices that have thin doped layers and also when mixed physics is used in the calculation. The mesh needs to be fine at and near the thin layer to capture rapid field or charge variations, but can coarsen away from these layers where field variations smoothen and charge densities are uniform. This poster will present an adaptive mesh refinement package that runs on parallel computers and is applied to specific microelectronic device simulations. Passive sensors that operate in the infrared portion of the spectrum as well as active device simulations that model charge transport and Maxwell's equations will be presented.

Effectiveness of Item Response Theory (IRT) Proficiency Estimation Methods under Adaptive Multistage Testing. Research Report. ETS RR-15-11

ERIC Educational Resources Information Center

Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry

2015-01-01

The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…

A New Approach to Parallel Dynamic Partitioning for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

Heber, Gerd; Biswas, Rupak; Gao, Guang R.

1999-01-01

Classical mesh partitioning algorithms were designed for rather static situations, and their straightforward application in a dynamical framework may lead to unsatisfactory results, e.g., excessive data migration among processors. Furthermore, special attention should be paid to their amenability to parallelization. In this paper, a novel parallel method for the dynamic partitioning of adaptive unstructured meshes is described. It is based on a linear representation of the mesh using self-avoiding walks.

Design and integration of ethnography within an international behavior change HIV/sexually transmitted disease prevention trial

PubMed Central

2008-01-01

Objective To use a common ethnographic study protocol across five countries to provide data to confirm social and risk settings and risk behaviors, develop the assessment instruments, tailor the intervention, design a process evaluation of the intervention, and design an understandable informed consent process. Design Methods determined best for capturing the core data elements were selected. Standards for data collection methods were established to enable comparable implementation of the ethnographic study across the five countries. Methods The methods selected were participant observation, focus groups, open-ended interviews, and social mapping. Standards included adhering to core data elements, number of participants, mode of data collection, type of data collection instrument, number of data collectors at each type of activity, duration of each type of activity, and type of informed consent administered. Sites had discretion in selecting which methods to use to obtain specific data. Results The ethnographic studies provided input to the Trial’s methods for data collection, described social groups in the target communities, depicted sexual practices, and determined core opinion leader characteristics; thus providing information that drove the adaptation of the intervention and facilitated the selection of venues, behavioral outcomes, and community popular opinion leaders (C-POLs). Conclusion The described rapid ethnographic approach worked well across the five countries, where findings allowed local adaptation of the intervention. When introducing the C-POL intervention in new areas, local non-governmental and governmental community and health workers can use this rapid ethnographic approach to identify the communities, social groups, messages, and C-POLs best suited for local implementation. PMID:17413263

Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches

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

Graf, Peter; Damiani, Rick R.; Dykes, Katherine

2017-01-09

A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the inputmore » parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into the already powerful importance sampling concept.« less

"Observation-Projet": A Professional Tool for Caregivers. Two Experiences in Italian Day-Care Settings

ERIC Educational Resources Information Center

Molina, Paola; Marotta, Monica; Bulgarelli, Daniela

2016-01-01

Ability to reflect on practice is a key element of early childhood professionalism and is positively associated with the quality of educational services. "Observation-Projet" (Fontaine 2008, 2011b) is a method designed to support practitioners' reflection through the observational process. The method adapts the required scientific…

Adapting an Outcome-Based Education Development Process to Meet Near Real-Time Challenges to Sustainable Agricultural Production

ERIC Educational Resources Information Center

Halbleib, Mary L.; Jepson, Paul C.

2015-01-01

Purpose: This paper examines the benefits of using an outcome-based education (OBE) method within agricultural extension outreach programmes for professional and farmer audiences. Design/Methodology/Approach: The method is elaborated through two practical examples, which show that focused, short-duration programmes can produce meaningful skill…

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

Harris, L.; Owel, W.R.

This paper discusses the VISA (Vulnerability of Integrated Safeguards Analysis) method, developed in 1976-77 for the Nuclear Regulatory Commission, and which has been adapted more recently to a broader range of uses. The performance of VISA systems is evaluated in terms of how they perform as an integrated safeguards/security system. The resulting method has been designated VISA-2. 7 refs.

Adaptation Design Tool for Climate-Smart Management of Coral Reefs and Other Natural Resources.

PubMed

West, Jordan M; Courtney, Catherine A; Hamilton, Anna T; Parker, Britt A; Gibbs, David A; Bradley, Patricia; Julius, Susan H

2018-06-22

Scientists and managers of natural resources have recognized an urgent need for improved methods and tools to enable effective adaptation of management measures in the face of climate change. This paper presents an Adaptation Design Tool that uses a structured approach to break down an otherwise overwhelming and complex process into tractable steps. The tool contains worksheets that guide users through a series of design considerations for adapting their planned management actions to be more climate-smart given changing environmental stressors. Also provided with other worksheets is a framework for brainstorming new adaptation options in response to climate threats not yet addressed in the current plan. Developed and tested in collaboration with practitioners in Hawai'i and Puerto Rico using coral reefs as a pilot ecosystem, the tool and associated reference materials consist of worksheets, instructions and lessons-learned from real-world examples. On the basis of stakeholder feedback from expert consultations during tool development, we present insights and recommendations regarding how to maximize tool efficiency, gain the greatest value from the thought process, and deal with issues of scale and uncertainty. We conclude by reflecting on how the tool advances the theory and practice of assessment and decision-making science, informs higher level strategic planning, and serves as a platform for a systematic, transparent and inclusive process to tackle the practical implications of climate change for management of natural resources.

Dynamic Experiment Design Regularization Approach to Adaptive Imaging with Array Radar/SAR Sensor Systems

PubMed Central

Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart

2011-01-01

We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the “model-free” variational analysis (VA)-based image enhancement approach and the “model-based” descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations. PMID:22163859

Sequential Multiple Assignment Randomized Trial (SMART) with Adaptive Randomization for Quality Improvement in Depression Treatment Program

PubMed Central

Chakraborty, Bibhas; Davidson, Karina W.

2015-01-01

Summary Implementation study is an important tool for deploying state-of-the-art treatments from clinical efficacy studies into a treatment program, with the dual goals of learning about effectiveness of the treatments and improving the quality of care for patients enrolled into the program. In this article, we deal with the design of a treatment program of dynamic treatment regimens (DTRs) for patients with depression post acute coronary syndrome. We introduce a novel adaptive randomization scheme for a sequential multiple assignment randomized trial of DTRs. Our approach adapts the randomization probabilities to favor treatment sequences having comparatively superior Q-functions used in Q-learning. The proposed approach addresses three main concerns of an implementation study: it allows incorporation of historical data or opinions, it includes randomization for learning purposes, and it aims to improve care via adaptation throughout the program. We demonstrate how to apply our method to design a depression treatment program using data from a previous study. By simulation, we illustrate that the inputs from historical data are important for the program performance measured by the expected outcomes of the enrollees, but also show that the adaptive randomization scheme is able to compensate poorly specified historical inputs by improving patient outcomes within a reasonable horizon. The simulation results also confirm that the proposed design allows efficient learning of the treatments by alleviating the curse of dimensionality. PMID:25354029

The application of virtual prototyping methods to determine the dynamic parameters of mobile robot

NASA Astrophysics Data System (ADS)

Kurc, Krzysztof; Szybicki, Dariusz; Burghardt, Andrzej; Muszyńska, Magdalena

2016-04-01

The paper presents methods used to determine the parameters necessary to build a mathematical model of an underwater robot with a crawler drive. The parameters present in the dynamics equation will be determined by means of advanced mechatronic design tools, including: CAD/CAE software andMES modules. The virtual prototyping process is described as well as the various possible uses (design adaptability) depending on the optional accessories added to the vehicle. A mathematical model is presented to show the kinematics and dynamics of the underwater crawler robot, essential for the design stage.

Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

PubMed Central

Hunt, Alexander; Szczecinski, Nicholas; Quinn, Roger

2017-01-01

Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal's body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even if the sensorimotor circuits were known in great detail, those parameters would not be applicable and new parameter values must be found for the network in the robotic model of the animal. This manuscript demonstrates an automatic method for setting parameter values in a synthetic nervous system composed of non-spiking leaky integrator neuron models. This method works by first using a model of the system to determine required motor neuron activations to produce stable walking. Parameters in the neural system are then tuned systematically such that it produces similar activations to the desired pattern determined using expected sensory feedback. We demonstrate that the developed method successfully produces adaptive locomotion in the rear legs of a dog-like robot actuated by artificial muscles. Furthermore, the results support the validity of current models of mammalian locomotion. This research will serve as a basis for testing more complex locomotion controllers and for testing specific sensory pathways and biomechanical designs. Additionally, the developed method can be used to automatically adapt the neural controller for different mechanical designs such that it could be used to control different robotic systems. PMID:28420977

Fully probabilistic control design in an adaptive critic framework.

PubMed

Herzallah, Randa; Kárný, Miroslav

2011-12-01

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Smartphone adapters for digital photomicrography

PubMed Central

Roy, Somak; Pantanowitz, Liron; Amin, Milon; Seethala, Raja R.; Ishtiaque, Ahmed; Yousem, Samuel A.; Parwani, Anil V.; Cucoranu, Ioan; Hartman, Douglas J.

2014-01-01

Background: Photomicrographs in Anatomic Pathology provide a means of quickly sharing information from a glass slide for consultation, education, documentation and publication. While static image acquisition historically involved the use of a permanently mounted camera unit on a microscope, such cameras may be expensive, need to be connected to a computer, and often require proprietary software to acquire and process images. Another novel approach for capturing digital microscopic images is to use smartphones coupled with the eyepiece of a microscope. Recently, several smartphone adapters have emerged that allow users to attach mobile phones to the microscope. The aim of this study was to test the utility of these various smartphone adapters. Materials and Methods: We surveyed the market for adapters to attach smartphones to the ocular lens of a conventional light microscope. Three adapters (Magnifi, Skylight and Snapzoom) were tested. We assessed the designs of these adapters and their effectiveness at acquiring static microscopic digital images. Results: All adapters facilitated the acquisition of digital microscopic images with a smartphone. The optimal adapter was dependent on the type of phone used. The Magnifi adapters for iPhone were incompatible when using a protective case. The Snapzoom adapter was easiest to use with iPhones and other smartphones even with protective cases. Conclusions: Smartphone adapters are inexpensive and easy to use for acquiring digital microscopic images. However, they require some adjustment by the user in order to optimize focus and obtain good quality images. Smartphone microscope adapters provide an economically feasible method of acquiring and sharing digital pathology photomicrographs. PMID:25191623

RF Pulse Design using Nonlinear Gradient Magnetic Fields

PubMed Central

Kopanoglu, Emre; Constable, R. Todd

2014-01-01

Purpose An iterative k-space trajectory and radio-frequency (RF) pulse design method is proposed for Excitation using Nonlinear Gradient Magnetic fields (ENiGMa). Theory and Methods The spatial encoding functions (SEFs) generated by nonlinear gradient fields (NLGFs) are linearly dependent in Cartesian-coordinates. Left uncorrected, this may lead to flip-angle variations in excitation profiles. In the proposed method, SEFs (k-space samples) are selected using a Matching-Pursuit algorithm, and the RF pulse is designed using a Conjugate-Gradient algorithm. Three variants of the proposed approach are given: the full-algorithm, a computationally-cheaper version, and a third version for designing spoke-based trajectories. The method is demonstrated for various target excitation profiles using simulations and phantom experiments. Results The method is compared to other iterative (Matching-Pursuit and Conjugate Gradient) and non-iterative (coordinate-transformation and Jacobian-based) pulse design methods as well as uniform density spiral and EPI trajectories. The results show that the proposed method can increase excitation fidelity significantly. Conclusion An iterative method for designing k-space trajectories and RF pulses using nonlinear gradient fields is proposed. The method can either be used for selecting the SEFs individually to guide trajectory design, or can be adapted to design and optimize specific trajectories of interest. PMID:25203286

Exploring factors influencing farmers' willingness to pay (WTP) for a planned adaptation programme to address climatic issues in agricultural sectors.

PubMed

Ahmed, Adeel; Masud, Muhammad Mehedi; Al-Amin, Abul Quasem; Yahaya, Siti Rohani Binti; Rahman, Mahfuzur; Akhtar, Rulia

2015-06-01

This study empirically estimates farmers' willingness to pay (WTP) for a planned adaptation programme for addressing climate issues in Pakistan's agricultural sectors. The contingent valuation method (CVM) was employed to determine a monetary valuation of farmers' preferences for a planned adaptation programme by ascertaining the value attached to address climatic issues. The survey was conducted by distributing structured questionnaires among Pakistani farmers. The study found that 67 % of respondents were willing to pay for a planned adaptation programme. However, several socioeconomic and motivational factors exert greater influence on their willingness to pay (WTP). This paper specifies the steps needed for all institutional bodies to better address issues in climate change. The outcomes of this paper will support attempts by policy makers to design an efficient adaptation framework for mitigating and adapting to the adverse impacts of climate change.

Estimating farmers' willingness to pay for climate change adaptation: the case of the Malaysian agricultural sector.

PubMed

Masud, Muhammad Mehedi; Junsheng, Ha; Akhtar, Rulia; Al-Amin, Abul Quasem; Kari, Fatimah Binti

2015-02-01

This paper estimates Malaysian farmers' willingness to pay (WTP) for a planned adaptation programme for addressing climate issues in the Malaysian agricultural sector. We used the contingent valuation method (CVM) for a monetary valuation of farmers' preferences for a planned adaptation programme by ascertaining the value attached to address climatic issues in the Malaysian agricultural sector. Structured questionnaires were distributed among the sampled farmers. The study found that 74 % of respondents were willing to pay for a planned adaptation programme and that several socioeconomic and motivation factors have greater influence on their WTP. This paper clearly specifies the steps needed for all institutional bodies to better address issues in climate change. The outcomes of this paper will support policy makers to better design an efficient adaptation framework for adapting to the adverse impacts of climate change.

Adaptive restoration of river terrace vegetation through iterative experiments

USGS Publications Warehouse

Dela Cruz, Michelle P.; Beauchamp, Vanessa B.; Shafroth, Patrick B.; Decker, Cheryl E.; O’Neil, Aviva

2014-01-01

Restoration projects can involve a high degree of uncertainty and risk, which can ultimately result in failure. An adaptive restoration approach can reduce uncertainty through controlled, replicated experiments designed to test specific hypotheses and alternative management approaches. Key components of adaptive restoration include willingness of project managers to accept the risk inherent in experimentation, interest of researchers, availability of funding for experimentation and monitoring, and ability to restore sites as iterative experiments where results from early efforts can inform the design of later phases. This paper highlights an ongoing adaptive restoration project at Zion National Park (ZNP), aimed at reducing the cover of exotic annual Bromus on riparian terraces, and revegetating these areas with native plant species. Rather than using a trial-and-error approach, ZNP staff partnered with academic, government, and private-sector collaborators to conduct small-scale experiments to explicitly address uncertainties concerning biomass removal of annual bromes, herbicide application rates and timing, and effective seeding methods for native species. Adaptive restoration has succeeded at ZNP because managers accept the risk inherent in experimentation and ZNP personnel are committed to continue these projects over a several-year period. Techniques that result in exotic annual Bromus removal and restoration of native plant species at ZNP can be used as a starting point for adaptive restoration projects elsewhere in the region.

Sliding-mode control combined with improved adaptive feedforward for wafer scanner

NASA Astrophysics Data System (ADS)

Li, Xiaojie; Wang, Yiguang

2018-03-01

In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

NASA Technical Reports Server (NTRS)

VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

2014-01-01

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

Adaptive optimization as a design and management methodology for coal-mining enterprise in uncertain and volatile market environment - the conceptual framework

NASA Astrophysics Data System (ADS)

Mikhalchenko, V. V.; Rubanik, Yu T.

2016-10-01

The work is devoted to the problem of cost-effective adaptation of coal mines to the volatile and uncertain market conditions. Conceptually it can be achieved through alignment of the dynamic characteristics of the coal mining system and power spectrum of market demand for coal product. In practical terms, this ensures the viability and competitiveness of coal mines. Transformation of dynamic characteristics is to be done by changing the structure of production system as well as corporate, logistics and management processes. The proposed methods and algorithms of control are aimed at the development of the theoretical foundations of adaptive optimization as basic methodology for coal mine enterprise management in conditions of high variability and uncertainty of economic and natural environment. Implementation of the proposed methodology requires a revision of the basic principles of open coal mining enterprises design.

Adapted RF pulse design for SAR reduction in parallel excitation with experimental verification at 9.4 T.

PubMed

Wu, Xiaoping; Akgün, Can; Vaughan, J Thomas; Andersen, Peter; Strupp, John; Uğurbil, Kâmil; Van de Moortele, Pierre-François

2010-07-01

Parallel excitation holds strong promises to mitigate the impact of large transmit B1 (B+1) distortion at very high magnetic field. Accelerated RF pulses, however, inherently tend to require larger values in RF peak power which may result in substantial increase in Specific Absorption Rate (SAR) in tissues, which is a constant concern for patient safety at very high field. In this study, we demonstrate adapted rate RF pulse design allowing for SAR reduction while preserving excitation target accuracy. Compared with other proposed implementations of adapted rate RF pulses, our approach is compatible with any k-space trajectories, does not require an analytical expression of the gradient waveform and can be used for large flip angle excitation. We demonstrate our method with numerical simulations based on electromagnetic modeling and we include an experimental verification of transmit pattern accuracy on an 8 transmit channel 9.4 T system.

Teaching older adults by adapting for aging changes.

PubMed

Weinrich, S P; Weinrich, M C; Boyd, M D; Atwood, J; Cervenka, B

1994-12-01

Few teaching programs are geared to meet the special learning needs of the elderly. This pilot study used a quasi-experimental pretest-posttest design to measure the effect of the Adaptation for Aging Changes (AAC) Method on fecal occult blood screening (FOBS) at meal sites for the elderly in the South. The AAC Method uses techniques that adjust the presentation to accommodate for normal aging changes and includes a demonstration of the procedure for collection of the stool blood test, memory reminders of the date to return the stool blood test, and written materials adapted to the 5th grade reading level. In addition, actual practice of the FOBS with the use of peanut butter was added to the AAC Method, making it the AAC with Practice Method (AACP) in two sites. The American Cancer Society's colorectal cancer educational slide-tape show served as the basis for all of the methods. Hemoccult II kits were distributed at no cost to the participants. Descriptive statistics, chi 2, and logistic regressions were used to analyze data from 135 Council on Aging meal sites' participants. The average age of the participants was 72 years; the average educational level was 8th grade; over half the sample was African-American; and half of the participants had incomes below the poverty level. Results support a significant increase in participation in FOBS in participants taught by the AACP Method [chi 2 (1, n = 56) = 5.34, p = 0.02; odds ratio = 6.2]. This research provides support for teaching that makes adaptations for aging changes, especially adaptations that include actual practice of the procedure.

Fully implicit moving mesh adaptive algorithm

NASA Astrophysics Data System (ADS)

Chacon, Luis

2005-10-01

In many problems of interest, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former is best dealt with with fully implicit methods, which are able to step over fast frequencies to resolve the dynamical time scale of interest. The latter requires grid adaptivity for efficiency. Moving-mesh grid adaptive methods are attractive because they can be designed to minimize the numerical error for a given resolution. However, the required grid governing equations are typically very nonlinear and stiff, and of considerably difficult numerical treatment. Not surprisingly, fully coupled, implicit approaches where the grid and the physics equations are solved simultaneously are rare in the literature, and circumscribed to 1D geometries. In this study, we present a fully implicit algorithm for moving mesh methods that is feasible for multidimensional geometries. A crucial element is the development of an effective multilevel treatment of the grid equation.ootnotetextL. Chac'on, G. Lapenta, A fully implicit, nonlinear adaptive grid strategy, J. Comput. Phys., accepted (2005) We will show that such an approach is competitive vs. uniform grids both from the accuracy (due to adaptivity) and the efficiency standpoints. Results for a variety of models 1D and 2D geometries, including nonlinear diffusion, radiation-diffusion, Burgers equation, and gas dynamics will be presented.

Community-based Participatory Process – Climate Change and Health Adaptation Program for Northern First Nations and Inuit in Canada

PubMed Central

Peace, Diane McClymont; Myers, Erin

2012-01-01

Objectives Health Canada's Program for Climate Change and Health Adaptation in Northern First Nation and Inuit Communities is unique among Canadian federal programs in that it enables community-based participatory research by northern communities. Study design The program was designed to build capacity by funding communities to conduct their own research in cooperation with Aboriginal associations, academics, and governments; that way, communities could develop health-related adaptation plans and communication materials that would help in adaptation decision-making at the community, regional, national and circumpolar levels with respect to human health and a changing environment. Methods Community visits and workshops were held to familiarize northerners with the impacts of climate change on their health, as well as methods to develop research proposals and budgets to meet program requirements. Results Since the launch of the Climate Change and Health Adaptation Program in 2008, Health Canada has funded 36 community projects across Canada's North that focus on relevant health issues caused by climate change. In addition, the program supported capacity-building workshops for northerners, as well as a Pan-Arctic Results Workshop to bring communities together to showcase the results of their research. Results include: numerous films and photo-voice products that engage youth and elders and are available on the web; community-based ice monitoring, surveillance and communication networks; and information products on land, water and ice safety, drinking water, food security and safety, and traditional medicine. Conclusions Through these efforts, communities have increased their knowledge and understanding of the health effects related to climate change and have begun to develop local adaptation strategies. PMID:22584509

An EMG-Based Control for an Upper-Limb Power-Assist Exoskeleton Robot.

PubMed

Kiguchi, K; Hayashi, Y

2012-08-01

Many kinds of power-assist robots have been developed in order to assist self-rehabilitation and/or daily life motions of physically weak persons. Several kinds of control methods have been proposed to control the power-assist robots according to user's motion intention. In this paper, an electromyogram (EMG)-based impedance control method for an upper-limb power-assist exoskeleton robot is proposed to control the robot in accordance with the user's motion intention. The proposed method is simple, easy to design, humanlike, and adaptable to any user. A neurofuzzy matrix modifier is applied to make the controller adaptable to any users. Not only the characteristics of EMG signals but also the characteristics of human body are taken into account in the proposed method. The effectiveness of the proposed method was evaluated by the experiments.

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1994-01-01

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

The Simulation of Magnetorheological Elastomers Adaptive Tuned Dynamic Vibration Absorber for Automobile Engine Vibration Control

NASA Astrophysics Data System (ADS)

Zhang, X. C.; Zhang, X. Z.; Li, W. H.; Liu, B.; Gong, X. L.; Zhang, P. Q.

The aim of this article is to investigate the use of a Dynamic Vibration Absorber to control vibration of engine by using simulation. Traditional means of vibration control have involved the use of passive and more recently, active methods. This study is different in that it involves an adaptive component in the design of vibration absorber using magnetorheological elastomers (MREs) as the adaptive spring. MREs are kind of novel smart material whose shear modulus can be controlled by applied magnetic field. In this paper, the vibration mode of a simple model of automobile engine is simulated by Finite Element Method (FEM) analysis. Based on the analysis, the MREs Adaptive Tuned Dynamic Vibration Absorber (ATDVA) is presented to reduce the vibration of the engine. Simulation result indicate that the control frequency of ATDVA can be changed by modifing the shear modulus of MREs and the vibraion reduction efficiency of ATDVA are also evaluated by FEM analysis.

Inclusive Competitive Game Play Through Balanced Sensory Feedback.

PubMed

Westin, Thomas; Söderström, David; Karlsson, Olov; Peiris, Ranil

2017-01-01

While game accessibility has improved significantly the last few years, there are still barriers for equal participation and multiplayer issues have been less researched. Game balance is here about making the game fair in a player versus player competitive game. One difficult design task is to balance the game to be fair regardless of visual or hearing capabilities, with clearly different requirements. This paper explores a tentative design method for enabling inclusive competitive game-play without individual adaptations of game rules that could spoil the game. The method involved applying a unified design method to design an unbalanced game, then modifying visual feedback as a hypothetical balanced design, and testing the game with totally 52 people with and without visual or hearing disabilities in three workshops. Game balance was evaluated based on score differences and less structured qualitative data, and a redesign of the game was made. Conclusions are a tentative method for balancing a multiplayer, competitive game without changing game rules and how the method can be applied.

Decoupling feedforward and feedback structures in hybrid active noise control systems for uncorrelated narrowband disturbances

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Burnett, Ian S.; Guo, Yecai

2015-08-01

Hybrid feedforward and feedback structures are useful for active noise control (ANC) applications where the noise can only be partially obtained with reference sensors. The traditional method uses the secondary signals of both the feedforward and feedback structures to synthesize a reference signal for the feedback structure in the hybrid structure. However, this approach introduces coupling between the feedforward and feedback structures and parameter changes in one structure affect the other during adaptation such that the feedforward and feedback structures must be optimized simultaneously in practical ANC system design. Two methods are investigated in this paper to remove such coupling effects. One is a simplified method, which uses the error signal directly as the reference signal in the feedback structure, and the second method generates the reference signal for the feedback structure by using only the secondary signal from the feedback structure and utilizes the generated reference signal as the error signal of the feedforward structure. Because the two decoupling methods can optimize the feedforward and feedback structures separately, they provide more flexibility in the design and optimization of the adaptive filters in practical ANC applications.

Solid oxide fuel cell anode image segmentation based on a novel quantum-inspired fuzzy clustering

NASA Astrophysics Data System (ADS)

Fu, Xiaowei; Xiang, Yuhan; Chen, Li; Xu, Xin; Li, Xi

2015-12-01

High quality microstructure modeling can optimize the design of fuel cells. For three-phase accurate identification of Solid Oxide Fuel Cell (SOFC) microstructure, this paper proposes a novel image segmentation method on YSZ/Ni anode Optical Microscopic (OM) images. According to Quantum Signal Processing (QSP), the proposed approach exploits a quantum-inspired adaptive fuzziness factor to adaptively estimate the energy function in the fuzzy system based on Markov Random Filed (MRF). Before defuzzification, a quantum-inspired probability distribution based on distance and gray correction is proposed, which can adaptively adjust the inaccurate probability estimation of uncertain points caused by noises and edge points. In this study, the proposed method improves accuracy and effectiveness of three-phase identification on the micro-investigation. It provides firm foundation to investigate the microstructural evolution and its related properties.

Sliding Window Generalized Kernel Affine Projection Algorithm Using Projection Mappings

NASA Astrophysics Data System (ADS)

Slavakis, Konstantinos; Theodoridis, Sergios

2008-12-01

Very recently, a solution to the kernel-based online classification problem has been given by the adaptive projected subgradient method (APSM). The developed algorithm can be considered as a generalization of a kernel affine projection algorithm (APA) and the kernel normalized least mean squares (NLMS). Furthermore, sparsification of the resulting kernel series expansion was achieved by imposing a closed ball (convex set) constraint on the norm of the classifiers. This paper presents another sparsification method for the APSM approach to the online classification task by generating a sequence of linear subspaces in a reproducing kernel Hilbert space (RKHS). To cope with the inherent memory limitations of online systems and to embed tracking capabilities to the design, an upper bound on the dimension of the linear subspaces is imposed. The underlying principle of the design is the notion of projection mappings. Classification is performed by metric projection mappings, sparsification is achieved by orthogonal projections, while the online system's memory requirements and tracking are attained by oblique projections. The resulting sparsification scheme shows strong similarities with the classical sliding window adaptive schemes. The proposed design is validated by the adaptive equalization problem of a nonlinear communication channel, and is compared with classical and recent stochastic gradient descent techniques, as well as with the APSM's solution where sparsification is performed by a closed ball constraint on the norm of the classifiers.

Sky coverage modeling for the whole sky for laser guide star multiconjugate adaptive optics.

PubMed

Wang, Lianqi; Andersen, David; Ellerbroek, Brent

2012-06-01

The scientific productivity of laser guide star adaptive optics systems strongly depends on the sky coverage, which describes the probability of finding natural guide stars for the tip/tilt wavefront sensor(s) to achieve a certain performance. Knowledge of the sky coverage is also important for astronomers planning their observations. In this paper, we present an efficient method to compute the sky coverage for the laser guide star multiconjugate adaptive optics system, the Narrow Field Infrared Adaptive Optics System (NFIRAOS), being designed for the Thirty Meter Telescope project. We show that NFIRAOS can achieve more than 70% sky coverage over most of the accessible sky with the requirement of 191 nm total rms wavefront.

Finite Element Analysis of Adaptive-Stiffening and Shape-Control SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Gao, Xiujie; Burton, Deborah; Turner, Travis L.; Brinson, Catherine

2005-01-01

Shape memory alloy hybrid composites with adaptive-stiffening or morphing functions are simulated using finite element analysis. The composite structure is a laminated fiber-polymer composite beam with embedded SMA ribbons at various positions with respect to the neutral axis of the beam. Adaptive stiffening or morphing is activated via selective resistance heating of the SMA ribbons or uniform thermal loads on the beam. The thermomechanical behavior of these composites was simulated in ABAQUS using user-defined SMA elements. The examples demonstrate the usefulness of the methods for the design and simulation of SMA hybrid composites. Keywords: shape memory alloys, Nitinol, ABAQUS, finite element analysis, post-buckling control, shape control, deflection control, adaptive stiffening, morphing, constitutive modeling, user element

Performance Optimizing Adaptive Control with Time-Varying Reference Model Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the performance optimization requirement obtained from an optimal control problem. The time-varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance metric. The effectiveness of the proposed method is demonstrated by an application of maneuver load alleviation control for a flexible aircraft.

Adaptive PID formation control of nonholonomic robots without leader's velocity information.

PubMed

Shen, Dongbin; Sun, Weijie; Sun, Zhendong

2014-03-01

This paper proposes an adaptive proportional integral derivative (PID) algorithm to solve a formation control problem in the leader-follower framework where the leader robot's velocities are unknown for the follower robots. The main idea is first to design some proper ideal control law for the formation system to obtain a required performance, and then to propose the adaptive PID methodology to approach the ideal controller. As a result, the formation is achieved with much more enhanced robust formation performance. The stability of the closed-loop system is theoretically proved by Lyapunov method. Both numerical simulations and physical vehicle experiments are presented to verify the effectiveness of the proposed adaptive PID algorithm. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Cost of riparian buffer zones: A comparison of hydrologically adapted site-specific riparian buffers with traditional fixed widths

NASA Astrophysics Data System (ADS)

Tiwari, T.; Lundström, J.; Kuglerová, L.; Laudon, H.; Öhman, K.; Ågren, A. M.

2016-02-01

Traditional approaches aiming at protecting surface waters from the negative impacts of forestry often focus on retaining fixed width buffer zones around waterways. While this method is relatively simple to design and implement, it has been criticized for ignoring the spatial heterogeneity of biogeochemical processes and biodiversity in the riparian zone. Alternatively, a variable width buffer zone adapted to site-specific hydrological conditions has been suggested to improve the protection of biogeochemical and ecological functions of the riparian zone. However, little is known about the monetary value of maintaining hydrologically adapted buffer zones compared to the traditionally used fixed width ones. In this study, we created a hydrologically adapted buffer zone by identifying wet areas and groundwater discharge hotspots in the riparian zone. The opportunity cost of the hydrologically adapted riparian buffer zones was then compared to that of the fixed width zones in a meso-scale boreal catchment to determine the most economical option of designing riparian buffers. The results show that hydrologically adapted buffer zones were cheaper per hectare than the fixed width ones when comparing the total cost. This was because the hydrologically adapted buffers included more wetlands and low productive forest areas than the fixed widths. As such, the hydrologically adapted buffer zones allows more effective protection of the parts of the riparian zones that are ecologically and biogeochemically important and more sensitive to disturbances without forest landowners incurring any additional cost than fixed width buffers.

Energy Conservation: A Management Report for State and Local Governments and A Technical Guide for State and Local Governments.

ERIC Educational Resources Information Center

Public Technology, Inc., Washington, DC.

This technical guide is part of a packet of tools designed to assist state or local government practitioners in organizing and managing an energy conservation program. It gives information on adapting energy conservation methods to existing public buildings and on designing new public buildings with energy conservation in mind. It also discusses…

Channel Estimation and Pilot Design for Massive MIMO Systems with Block-Structured Compressive Sensing

NASA Astrophysics Data System (ADS)

Lv, ZhuoKai; Yang, Tiejun; Zhu, Chunhua

2018-03-01

Through utilizing the technology of compressive sensing (CS), the channel estimation methods can achieve the purpose of reducing pilots and improving spectrum efficiency. The channel estimation and pilot design scheme are explored during the correspondence under the help of block-structured CS in massive MIMO systems. The block coherence property of the aggregate system matrix can be minimized so that the pilot design scheme based on stochastic search is proposed. Moreover, the block sparsity adaptive matching pursuit (BSAMP) algorithm under the common sparsity model is proposed so that the channel estimation can be caught precisely. Simulation results are to be proved the proposed design algorithm with superimposed pilots design and the BSAMP algorithm can provide better channel estimation than existing methods.

New head gradient coil design and construction techniques.

PubMed

Handler, William B; Harris, Chad T; Scholl, Timothy J; Parker, Dennis L; Goodrich, K Craig; Dalrymple, Brian; Van Sass, Frank; Chronik, Blaine A

2014-05-01

To design and build a head insert gradient coil to use in conjunction with body gradients for superior imaging. The use of the boundary element method to solve for a gradient coil wire pattern on an arbitrary surface allowed us to incorporate engineering changes into the electromagnetic design of a gradient coil directly. Improved wire pattern design was combined with robust manufacturing techniques and novel cooling methods. The finished coil had an efficiency of 0.15 mT/m/A in all three axes and allowed the imaging region to extend across the entire head and upper part of the neck. The ability to adapt an electromagnetic design to necessary changes from an engineering perspective leads to superior coil performance. Copyright © 2013 Wiley Periodicals, Inc.

Adaptive hybrid control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2018-06-01

To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

Spacewire router IP-core with priority adaptive routing

NASA Astrophysics Data System (ADS)

Shakhmatov, A. V.; Chekmarev, S. A.; Vergasov, M. Y.; Khanov, V. Kh

2015-10-01

Design of modern spacecraft focuses on using network principles of interaction on-board equipment, in particular in network SpaceWire. Routers are an integral part of most SpaceWire networks. The paper presents an adaptive routing algorithm with a prioritization, allowing more flexibility to manage the routing process. This algorithm is designed to transmit SpaceWire packets over a redundant network. Also a method is proposed for rapid restoration of working capacity after power by saving the routing table and the router configuration in an external non-volatile memory. The proposed solutions used to create IP-core router, and then tested in the FPGA device. The results illustrate the realizability and rationality of the proposed solutions.

Self-tuning control of attitude and momentum management for the Space Station

NASA Technical Reports Server (NTRS)

Shieh, L. S.; Sunkel, J. W.; Yuan, Z. Z.; Zhao, X. M.

1992-01-01

This paper presents a hybrid state-space self-tuning design methodology using dual-rate sampling for suboptimal digital adaptive control of attitude and momentum management for the Space Station. This new hybrid adaptive control scheme combines an on-line recursive estimation algorithm for indirectly identifying the parameters of a continuous-time system from the available fast-rate sampled data of the inputs and states and a controller synthesis algorithm for indirectly finding the slow-rate suboptimal digital controller from the designed optimal analog controller. The proposed method enables the development of digitally implementable control algorithms for the robust control of Space Station Freedom with unknown environmental disturbances and slowly time-varying dynamics.

Cockpit Adaptive Automation and Pilot Performance

NASA Technical Reports Server (NTRS)

Parasuraman, Raja

2001-01-01

The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals were met or exceeded. The results of the research extended knowledge of automation-related performance decrements in pilots and demonstrated the positive effects of adaptive task allocation. In addition, several practical implications for cockpit automation design were drawn from the research conducted. A total of 12 articles deriving from the project were published.

Study of Subway Station Design and Construction

DOT National Transportation Integrated Search

1977-03-01

Due to the high cost of urban underground transit construction in recent years, construction practices used in other countries were reviewed to determine if construction methods which are commonly accepted there might be adapted to U.S. practice. Des...

Multiple imputation of missing data in nested case-control and case-cohort studies.

PubMed

Keogh, Ruth H; Seaman, Shaun R; Bartlett, Jonathan W; Wood, Angela M

2018-06-05

The nested case-control and case-cohort designs are two main approaches for carrying out a substudy within a prospective cohort. This article adapts multiple imputation (MI) methods for handling missing covariates in full-cohort studies for nested case-control and case-cohort studies. We consider data missing by design and data missing by chance. MI analyses that make use of full-cohort data and MI analyses based on substudy data only are described, alongside an intermediate approach in which the imputation uses full-cohort data but the analysis uses only the substudy. We describe adaptations to two imputation methods: the approximate method (MI-approx) of White and Royston () and the "substantive model compatible" (MI-SMC) method of Bartlett et al. (). We also apply the "MI matched set" approach of Seaman and Keogh () to nested case-control studies, which does not require any full-cohort information. The methods are investigated using simulation studies and all perform well when their assumptions hold. Substantial gains in efficiency can be made by imputing data missing by design using the full-cohort approach or by imputing data missing by chance in analyses using the substudy only. The intermediate approach brings greater gains in efficiency relative to the substudy approach and is more robust to imputation model misspecification than the full-cohort approach. The methods are illustrated using the ARIC Study cohort. Supplementary Materials provide R and Stata code. © 2018, The International Biometric Society.

An adaptive model for vanadium redox flow battery and its application for online peak power estimation

NASA Astrophysics Data System (ADS)

Wei, Zhongbao; Meng, Shujuan; Tseng, King Jet; Lim, Tuti Mariana; Soong, Boon Hee; Skyllas-Kazacos, Maria

2017-03-01

An accurate battery model is the prerequisite for reliable state estimate of vanadium redox battery (VRB). As the battery model parameters are time varying with operating condition variation and battery aging, the common methods where model parameters are empirical or prescribed offline lacks accuracy and robustness. To address this issue, this paper proposes to use an online adaptive battery model to reproduce the VRB dynamics accurately. The model parameters are online identified with both the recursive least squares (RLS) and the extended Kalman filter (EKF). Performance comparison shows that the RLS is superior with respect to the modeling accuracy, convergence property, and computational complexity. Based on the online identified battery model, an adaptive peak power estimator which incorporates the constraints of voltage limit, SOC limit and design limit of current is proposed to fully exploit the potential of the VRB. Experiments are conducted on a lab-scale VRB system and the proposed peak power estimator is verified with a specifically designed "two-step verification" method. It is shown that different constraints dominate the allowable peak power at different stages of cycling. The influence of prediction time horizon selection on the peak power is also analyzed.

Adaptive dynamic programming approach to experience-based systems identification and control.

PubMed

Lendaris, George G

2009-01-01

Humans have the ability to make use of experience while selecting their control actions for distinct and changing situations, and their process speeds up and have enhanced effectiveness as more experience is gained. In contrast, current technological implementations slow down as more knowledge is stored. A novel way of employing Approximate (or Adaptive) Dynamic Programming (ADP) is described that shifts the underlying Adaptive Critic type of Reinforcement Learning method "up a level", away from designing individual (optimal) controllers to that of developing on-line algorithms that efficiently and effectively select designs from a repository of existing controller solutions (perhaps previously developed via application of ADP methods). The resulting approach is called Higher-Level Learning Algorithm. The approach and its rationale are described and some examples of its application are given. The notions of context and context discernment are important to understanding the human abilities noted above. These are first defined, in a manner appropriate to controls and system-identification, and as a foundation relating to the application arena, a historical view of the various phases during development of the controls field is given, organized by how the notion 'context' was, or was not, involved in each phase.

Lack of Interaction between Sensing-Intuitive Learning Styles and Problem-First versus Information-First Instruction: A Randomized Crossover Trial

ERIC Educational Resources Information Center

Cook, David A.; Thompson, Warren G.; Thomas, Kris G.; Thomas, Matthew R.

2009-01-01

Background: Adaptation to learning styles has been proposed to enhance learning. Objective: We hypothesized that learners with sensing learning style would perform better using a problem-first instructional method while intuitive learners would do better using an information-first method. Design: Randomized, controlled, crossover trial. Setting:…

Adaptive cluster sampling: An efficient method for assessing inconspicuous species

Treesearch

Andrea M. Silletti; Joan Walker

2003-01-01

Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

2017-12-01

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

Meta-analyses and adaptive group sequential designs in the clinical development process.

PubMed

Jennison, Christopher; Turnbull, Bruce W

2005-01-01

The clinical development process can be viewed as a succession of trials, possibly overlapping in calendar time. The design of each trial may be influenced by results from previous studies and other currently proceeding trials, as well as by external information. Results from all of these trials must be considered together in order to assess the efficacy and safety of the proposed new treatment. Meta-analysis techniques provide a formal way of combining the information. We examine how such methods can be used in combining results from: (1) a collection of separate studies, (2) a sequence of studies in an organized development program, and (3) stages within a single study using a (possibly adaptive) group sequential design. We present two examples. The first example concerns the combining of results from a Phase IIb trial using several dose levels or treatment arms with those of the Phase III trial comparing the treatment selected in Phase IIb against a control This enables a "seamless transition" from Phase IIb to Phase III. The second example examines the use of combination tests to analyze data from an adaptive group sequential trial.

Novel adaptive neural control design for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

NASA Astrophysics Data System (ADS)

Bu, Xiangwei; Wu, Xiaoyan; He, Guangjun; Huang, Jiaqi

2016-03-01

This paper investigates the design of a novel adaptive neural controller for the longitudinal dynamics of a flexible air-breathing hypersonic vehicle with control input constraints. To reduce the complexity of controller design, the vehicle dynamics is decomposed into the velocity subsystem and the altitude subsystem, respectively. For each subsystem, only one neural network is utilized to approach the lumped unknown function. By employing a minimal-learning parameter method to estimate the norm of ideal weight vectors rather than their elements, there are only two adaptive parameters required for neural approximation. Thus, the computational burden is lower than the ones derived from neural back-stepping schemes. Specially, to deal with the control input constraints, additional systems are exploited to compensate the actuators. Lyapunov synthesis proves that all the closed-loop signals involved are uniformly ultimately bounded. Finally, simulation results show that the adopted compensation scheme can tackle actuator constraint effectively and moreover velocity and altitude can stably track their reference trajectories even when the physical limitations on control inputs are in effect.

Design of infrasound-detection system via adaptive LMSTDE algorithm

NASA Technical Reports Server (NTRS)

Khalaf, C. S.; Stoughton, J. W.

1984-01-01

A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.

Factors associated with adaptation to Klinefelter syndrome: The experience of adolescents and adults

PubMed Central

Turriff, Amy; Levy, Howard P.; Biesecker, Barbara

2016-01-01

Objective The purpose of this study was to understand the impact of living with Klinefelter syndrome (XXY) as an adolescent or an adult and to examine the factors that contribute to adaptation. Methods Individuals (n = 310) aged 14–75 years with self-reported XXY were recruited from online support networks to complete a self-administered survey. Perceived consequences, perceived severity, perceived stigma, and coping were measured and evaluated as correlates of adaptation. Results The use of problem-focused coping strategies was positively correlated with adaptation (p < 0.01) and age was negatively correlated with adaptation (p < 0.05). Conclusion The majority of participants reported significant negative consequences of XXY, including infertility, psychological co-morbidities and differences in appearance. How participants coped with their negative appraisals was the greatest predictor of adaptation. Practice implications Interventions designed to help individuals reframe negative appraisals, to increase perceived manageability of the challenges of living with XXY, and to facilitate effective coping may improve adaptation among individuals with XXY. PMID:25239793

Adaptive Fading Memory H∞ Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors

NASA Astrophysics Data System (ADS)

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

2015-08-01

The paper deals with dynamic compensation of delayed Self Powered Flux Detectors (SPFDs) using discrete time H∞ filtering method for improving the response of SPFDs with significant delayed components such as Platinum and Vanadium SPFD. We also present a comparative study between the Linear Matrix Inequality (LMI) based H∞ filtering and Algebraic Riccati Equation (ARE) based Kalman filtering methods with respect to their delay compensation capabilities. Finally an improved recursive H∞ filter based on the adaptive fading memory technique is proposed which provides an improved performance over existing methods. The existing delay compensation algorithms do not account for the rate of change in the signal for determining the filter gain and therefore add significant noise during the delay compensation process. The proposed adaptive fading memory H∞ filter minimizes the overall noise very effectively at the same time keeps the response time at minimum values. The recursive algorithm is easy to implement in real time as compared to the LMI (or ARE) based solutions.

Advanced adaptive computational methods for Navier-Stokes simulations in rotorcraft aerodynamics

NASA Technical Reports Server (NTRS)

Stowers, S. T.; Bass, J. M.; Oden, J. T.

1993-01-01

A phase 2 research and development effort was conducted in area transonic, compressible, inviscid flows with an ultimate goal of numerically modeling complex flows inherent in advanced helicopter blade designs. The algorithms and methodologies therefore are classified as adaptive methods, which are error estimation techniques for approximating the local numerical error, and automatically refine or unrefine the mesh so as to deliver a given level of accuracy. The result is a scheme which attempts to produce the best possible results with the least number of grid points, degrees of freedom, and operations. These types of schemes automatically locate and resolve shocks, shear layers, and other flow details to an accuracy level specified by the user of the code. The phase 1 work involved a feasibility study of h-adaptive methods for steady viscous flows, with emphasis on accurate simulation of vortex initiation, migration, and interaction. Phase 2 effort focused on extending these algorithms and methodologies to a three-dimensional topology.

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

NASA Astrophysics Data System (ADS)

Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

2017-09-01

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

A practical globalization of one-shot optimization for optimal design of tokamak divertors

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

Blommaert, Maarten, E-mail: maarten.blommaert@kuleuven.be; Dekeyser, Wouter; Baelmans, Martine

In past studies, nested optimization methods were successfully applied to design of the magnetic divertor configuration in nuclear fusion reactors. In this paper, so-called one-shot optimization methods are pursued. Due to convergence issues, a globalization strategy for the one-shot solver is sought. Whereas Griewank introduced a globalization strategy using a doubly augmented Lagrangian function that includes primal and adjoint residuals, its practical usability is limited by the necessity of second order derivatives and expensive line search iterations. In this paper, a practical alternative is offered that avoids these drawbacks by using a regular augmented Lagrangian merit function that penalizes onlymore » state residuals. Additionally, robust rank-two Hessian estimation is achieved by adaptation of Powell's damped BFGS update rule. The application of the novel one-shot approach to magnetic divertor design is considered in detail. For this purpose, the approach is adapted to be complementary with practical in parts adjoint sensitivities. Using the globalization strategy, stable convergence of the one-shot approach is achieved.« less

Bayesian randomized clinical trials: From fixed to adaptive design.

PubMed

Yin, Guosheng; Lam, Chi Kin; Shi, Haolun

2017-08-01

Randomized controlled studies are the gold standard for phase III clinical trials. Using α-spending functions to control the overall type I error rate, group sequential methods are well established and have been dominating phase III studies. Bayesian randomized design, on the other hand, can be viewed as a complement instead of competitive approach to the frequentist methods. For the fixed Bayesian design, the hypothesis testing can be cast in the posterior probability or Bayes factor framework, which has a direct link to the frequentist type I error rate. Bayesian group sequential design relies upon Bayesian decision-theoretic approaches based on backward induction, which is often computationally intensive. Compared with the frequentist approaches, Bayesian methods have several advantages. The posterior predictive probability serves as a useful and convenient tool for trial monitoring, and can be updated at any time as the data accrue during the trial. The Bayesian decision-theoretic framework possesses a direct link to the decision making in the practical setting, and can be modeled more realistically to reflect the actual cost-benefit analysis during the drug development process. Other merits include the possibility of hierarchical modeling and the use of informative priors, which would lead to a more comprehensive utilization of information from both historical and longitudinal data. From fixed to adaptive design, we focus on Bayesian randomized controlled clinical trials and make extensive comparisons with frequentist counterparts through numerical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

Coordinating IMC-PID and adaptive SMC controllers for a PEMFC.

PubMed

Wang, Guo-Liang; Wang, Yong; Shi, Jun-Hai; Shao, Hui-He

2010-01-01

For a Proton Exchange Membrane Fuel Cell (PEMFC) power plant with a methanol reformer, the process parameters and power output are considered simultaneously to avoid violation of the constraints and to keep the fuel cell power plant safe and effective. In this paper, a novel coordinating scheme is proposed by combining an Internal Model Control (IMC) based PID Control and adaptive Sliding Mode Control (SMC). The IMC-PID controller is designed for the reformer of the fuel flow rate according to the expected first-order dynamic properties. The adaptive SMC controller of the fuel cell current has been designed using the constant plus proportional rate reaching law. The parameters of the SMC controller are adaptively tuned according to the response of the fuel flow rate control system. When the power output controller feeds back the current references to these two controllers, the coordinating controllers system works in a system-wide way. The simulation results of the PEMFC power plant demonstrate the effectiveness of the proposed method. 2009 ISA. Published by Elsevier Ltd. All rights reserved.

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

Time-to-event continual reassessment method incorporating treatment cycle information with application to an oncology phase I trial.

PubMed

Huang, Bo; Kuan, Pei Fen

2014-11-01

Delayed dose limiting toxicities (i.e. beyond first cycle of treatment) is a challenge for phase I trials. The time-to-event continual reassessment method (TITE-CRM) is a Bayesian dose-finding design to address the issue of long observation time and early patient drop-out. It uses a weighted binomial likelihood with weights assigned to observations by the unknown time-to-toxicity distribution, and is open to accrual continually. To avoid dosing at overly toxic levels while retaining accuracy and efficiency for DLT evaluation that involves multiple cycles, we propose an adaptive weight function by incorporating cyclical data of the experimental treatment with parameters updated continually. This provides a reasonable estimate for the time-to-toxicity distribution by accounting for inter-cycle variability and maintains the statistical properties of consistency and coherence. A case study of a First-in-Human trial in cancer for an experimental biologic is presented using the proposed design. Design calibrations for the clinical and statistical parameters are conducted to ensure good operating characteristics. Simulation results show that the proposed TITE-CRM design with adaptive weight function yields significantly shorter trial duration, does not expose patients to additional risk, is competitive against the existing weighting methods, and possesses some desirable properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Test Information Targeting Strategies for Adaptive Multistage Testing Designs.

ERIC Educational Resources Information Center

Luecht, Richard M.; Burgin, William

Adaptive multistage testlet (MST) designs appear to be gaining popularity for many large-scale computer-based testing programs. These adaptive MST designs use a modularized configuration of preconstructed testlets and embedded score-routing schemes to prepackage different forms of an adaptive test. The conditional information targeting (CIT)…

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.

Empirical evaluation of a virtual laboratory approach to teach lactate dehydrogenase enzyme kinetics.

PubMed

Booth, Christine; Cheluvappa, Rajkumar; Bellinson, Zack; Maguire, Danni; Zimitat, Craig; Abraham, Joyce; Eri, Rajaraman

2016-06-01

Personalised instruction is increasingly recognised as crucial for efficacious learning today. Our seminal work delineates and elaborates on the principles, development and implementation of a specially-designed adaptive, virtual laboratory. We strived to teach laboratory skills associated with lactate dehydrogenase (LDH) enzyme kinetics to 2nd-year biochemistry students using our adaptive learning platform. Pertinent specific aims were to:(1)design/implement a web-based lesson to teach lactate dehydrogenase(LDH) enzyme kinetics to 2nd-year biochemistry students(2)determine its efficacious in improving students' comprehension of enzyme kinetics(3)assess their perception of its usefulness/manageability(vLab versus Conventional Tutorial). Our tools were designed using HTML5 technology. We hosted the program on an adaptive e-learning platform (AeLP). Provisions were made to interactively impart informed laboratory skills associated with measuring LDH enzyme kinetics. A series of e-learning methods were created. Tutorials were generated for interactive teaching and assessment. The learning outcomes herein were on par with that from a conventional classroom tutorial. Student feedback showed that the majority of students found the vLab learning experience "valuable"; and the vLab format/interface "well-designed". However, there were a few technical issues with the 1st roll-out of the platform. Our pioneering effort resulted in productive learning with the vLab, with parity with that from a conventional tutorial. Our contingent discussion emphasises not only the cornerstone advantages, but also the shortcomings of the AeLP method utilised. We conclude with an astute analysis of possible extensions and applications of our methodology.

Design of Rail Instrumentation for Wind Tunnel Sonic Boom Measurements and Computational-Experimental Comparisons

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Elmiligui, A.; Aftosmis, M.; Morgenstern, J.; Durston, D.; Thomas, S.

2012-01-01

An innovative pressure rail concept for wind tunnel sonic boom testing of modern aircraft configurations with very low overpressures was designed with an adjoint-based solution-adapted Cartesian grid method. The computational method requires accurate free-air calculations of a test article as well as solutions modeling the influence of rail and tunnel walls. Specialized grids for accurate Euler and Navier-Stokes sonic boom computations were used on several test articles including complete aircraft models with flow-through nacelles. The computed pressure signatures are compared with recent results from the NASA 9- x 7-foot Supersonic Wind Tunnel using the advanced rail design.

Feedback system design with an uncertain plant

NASA Technical Reports Server (NTRS)

Milich, D.; Valavani, L.; Athans, M.

1986-01-01

A method is developed to design a fixed-parameter compensator for a linear, time-invariant, SISO (single-input single-output) plant model characterized by significant structured, as well as unstructured, uncertainty. The controller minimizes the H(infinity) norm of the worst-case sensitivity function over the operating band and the resulting feedback system exhibits robust stability and robust performance. It is conjectured that such a robust nonadaptive control design technique can be used on-line in an adaptive control system.

Advances in adaptive control theory: Gradient- and derivative-free approaches

NASA Astrophysics Data System (ADS)

Yucelen, Tansel

In this dissertation, we present new approaches to improve standard designs in adaptive control theory, and novel adaptive control architectures. We first present a novel Kalman filter based approach for approximately enforcing a linear constraint in standard adaptive control design. One application is that this leads to alternative forms for well known modification terms such as e-modification. In addition, it leads to smaller tracking errors without incurring significant oscillations in the system response and without requiring high modification gain. We derive alternative forms of e- and adaptive loop recovery (ALR-) modifications. Next, we show how to use Kalman filter optimization to derive a novel adaptation law. This results in an optimization-based time-varying adaptation gain that reduces the need for adaptation gain tuning. A second major contribution of this dissertation is the development of a novel derivative-free, delayed weight update law for adaptive control. The assumption of constant unknown ideal weights is relaxed to the existence of time-varying weights, such that fast and possibly discontinuous variation in weights are allowed. This approach is particulary advantageous for applications to systems that can undergo a sudden change in dynamics, such as might be due to reconfiguration, deployment of a payload, docking, or structural damage, and for rejection of external disturbance processes. As a third and final contribution, we develop a novel approach for extending all the methods developed in this dissertation to the case of output feedback. The approach is developed only for the case of derivative-free adaptive control, and the extension of the other approaches developed previously for the state feedback case to output feedback is left as a future research topic. The proposed approaches of this dissertation are illustrated in both simulation and flight test.

Towards a Framework for Modeling Space Systems Architectures

NASA Technical Reports Server (NTRS)

Shames, Peter; Skipper, Joseph

2006-01-01

Topics covered include: 1) Statement of the problem: a) Space system architecture is complex; b) Existing terrestrial approaches must be adapted for space; c) Need a common architecture methodology and information model; d) Need appropriate set of viewpoints. 2) Requirements on a space systems model. 3) Model Based Engineering and Design (MBED) project: a) Evaluated different methods; b) Adapted and utilized RASDS & RM-ODP; c) Identified useful set of viewpoints; d) Did actual model exchanges among selected subset of tools. 4) Lessons learned & future vision.

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

Pierson, L.G.; Witzke, E.L.

This effort studied the integration of innovative methods of key management crypto synchronization, and key agility while scaling encryption speed. Viability of these methods for encryption of ATM cell payloads at the SONET OC- 192 data rate (10 Gb/s), and for operation at OC-48 rates (2.5 Gb/s) was shown. An SNL-Developed pipelined DES design was adapted for the encryption of ATM cells. A proof-of-principle prototype circuit board containing 11 Electronically Programmable Logic Devices (each holding the equivalent of 100,000 gates) was designed, built, and used to prototype a high speed encryptor.

Isothermic and fixed intensity heat acclimation methods induce similar heat adaptation following short and long-term timescales.

PubMed

Gibson, Oliver R; Mee, Jessica A; Tuttle, James A; Taylor, Lee; Watt, Peter W; Maxwell, Neil S

2015-01-01

Heat acclimation requires the interaction between hot environments and exercise to elicit thermoregulatory adaptations. Optimal synergism between these parameters is unknown. Common practise involves utilising a fixed workload model where exercise prescription is controlled and core temperature is uncontrolled, or an isothermic model where core temperature is controlled and work rate is manipulated to control core temperature. Following a baseline heat stress test; 24 males performed a between groups experimental design performing short term heat acclimation (STHA; five 90 min sessions) and long term heat acclimation (LTHA; STHA plus further five 90 min sessions) utilising either fixed intensity (50% VO2peak), continuous isothermic (target rectal temperature 38.5 °C for STHA and LTHA), or progressive isothermic heat acclimation (target rectal temperature 38.5 °C for STHA, and 39.0 °C for LTHA). Identical heat stress tests followed STHA and LTHA to determine the magnitude of adaptation. All methods induced equal adaptation from baseline however isothermic methods induced adaptation and reduced exercise durations (STHA = -66% and LTHA = -72%) and mean session intensity (STHA = -13% VO2peak and LTHA = -9% VO2peak) in comparison to fixed (p < 0.05). STHA decreased exercising heart rate (-10 b min(-1)), core (-0.2 °C) and skin temperature (-0.51 °C), with sweat losses increasing (+0.36 Lh(-1)) (p<0.05). No difference between heat acclimation methods, and no further benefit of LTHA was observed (p > 0.05). Only thermal sensation improved from baseline to STHA (-0.2), and then between STHA and LTHA (-0.5) (p<0.05). Both the continuous and progressive isothermic methods elicited exercise duration, mean session intensity, and mean T(rec) analogous to more efficient administration for maximising adaptation. Short term isothermic methods are therefore optimal for individuals aiming to achieve heat adaptation most economically, i.e. when integrating heat acclimation into a pre-competition taper. Fixed methods may be optimal for military and occupational applications due to lower exercise intensity and simplified administration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Work Domain Analysis Methodology for Development of Operational Concepts for Advanced Reactors

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

Hugo, Jacques

2015-05-01

This report describes a methodology to conduct a Work Domain Analysis in preparation for the development of operational concepts for new plants. This method has been adapted from the classical method described in the literature in order to better deal with the uncertainty and incomplete information typical of first-of-a-kind designs. The report outlines the strategy for undertaking a Work Domain Analysis of a new nuclear power plant and the methods to be used in the development of the various phases of the analysis. Basic principles are described to the extent necessary to explain why and how the classical method wasmore » adapted to make it suitable as a tool for the preparation of operational concepts for a new nuclear power plant. Practical examples are provided of the systematic application of the method and the various presentation formats in the operational analysis of advanced reactors.« less

The Distributed Lambda (?) Model (DLM): A 3-D, Finite-Element Muscle Model Based on Feldman's ? Model; Assessment of Orofacial Gestures

ERIC Educational Resources Information Center

Nazari, Mohammad Ali; Perrier, Pascal; Payan, Yohan

2013-01-01

Purpose: The authors aimed to design a distributed lambda model (DLM), which is well adapted to implement three-dimensional (3-D), finite-element descriptions of muscles. Method: A muscle element model was designed. Its stress-strain relationships included the active force-length characteristics of the ? model along the muscle fibers, together…

An efficient adaptive sampling strategy for global surrogate modeling with applications in multiphase flow simulation

NASA Astrophysics Data System (ADS)

Mo, S.; Lu, D.; Shi, X.; Zhang, G.; Ye, M.; Wu, J.

2016-12-01

Surrogate models have shown remarkable computational efficiency in hydrological simulations involving design space exploration, sensitivity analysis, uncertainty quantification, etc. The central task of constructing a global surrogate models is to achieve a prescribed approximation accuracy with as few original model executions as possible, which requires a good design strategy to optimize the distribution of data points in the parameter domains and an effective stopping criterion to automatically terminate the design process when desired approximation accuracy is achieved. This study proposes a novel adaptive sampling strategy, which starts from a small number of initial samples and adaptively selects additional samples by balancing the collection in unexplored regions and refinement in interesting areas. We define an efficient and effective evaluation metric basing on Taylor expansion to select the most promising potential samples from candidate points, and propose a robust stopping criterion basing on the approximation accuracy at new points to guarantee the achievement of desired accuracy. The numerical results of several benchmark analytical functions indicate that the proposed approach is more computationally efficient and robust than the widely used maximin distance design and two other well-known adaptive sampling strategies. The application to two complicated multiphase flow problems further demonstrates the efficiency and effectiveness of our method in constructing global surrogate models for high-dimensional and highly nonlinear problems. Acknowledgements: This work was financially supported by the National Nature Science Foundation of China grants No. 41030746 and 41172206.

Adaptive Optimal Control Using Frequency Selective Information of the System Uncertainty With Application to Unmanned Aircraft.

PubMed

Maity, Arnab; Hocht, Leonhard; Heise, Christian; Holzapfel, Florian

2018-01-01

A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input effectiveness failures or damages. For adaptation of the unknown parameters of these uncertainties, the frequency selective learning approach is used. Its idea is to compute a filtered expression of the system uncertainty using multiple filters based on online instantaneous information, which is used for augmentation of the update law. It is capable of adjusting a sudden change in system dynamics without depending on high adaptation gains and can satisfy exponential parameter error convergence under certain conditions in the presence of structured matched and unmatched uncertainties as well. Additionally, the controller of the MRAC system is designed using a new optimal control method. This method is a new linear quadratic regulator-based optimal control formulation for both output regulation and command tracking problems. It provides a closed-form control solution. The proposed overall approach is applied in a control of lateral dynamics of an unmanned aircraft problem to show its effectiveness.

The practical application of adaptive study design in early phase clinical trials: a retrospective analysis of time savings.

PubMed

Lorch, U; Berelowitz, K; Ozen, C; Naseem, A; Akuffo, E; Taubel, J

2012-05-01

The interest in adaptive study design is evident from the growing amount of clinical research employing this model in the mid to later stages of medicines development. Little has been published on the practical application and merits of adaptive study design in early phase clinical research. This paper describes a retrospective analysis performed on a sample of 29 industry lead adaptive early phase studies commencing between 1 January 2006 and 31 December 2010 in a clinical trials unit in London, England. All studies containing at least one adaptive feature in the original protocol were included in the analysis. The scope of the analysis was to assess whether the use of adaptive study designs provided tangible benefits over the use of conventional study designs using time savings as the main measure. We conclude that the use of adaptive study design saves time in early phase research programs. This is achieved by abolishing the need for substantial amendments or by mitigating their impact on timelines and by using adaptive scheduling efficiencies.

Application of Taguchi methods to infrared window design

NASA Astrophysics Data System (ADS)

Osmer, Kurt A.; Pruszynski, Charles J.

1990-10-01

Dr. Genichi Taguchi, a prominent quality consultant, reduced a branch of statistics known as "Design of Experiments" to a cookbook methodology that can be employed by any competent engineer. This technique has been extensively employed by Japanese manufacturers, and is widely credited with helping them attain their current level of success in low cost, high quality product design and fabrication. Although this technique was originally put forth as a tool to streamline the determination of improved production processes, it can also be applied to a wide range of engineering problems. As part of an internal research project, this method of experimental design has been adapted to window trade studies and materials research. Two of these analyses are presented herein, and have been chosen to illustrate the breadth of applications to which the Taguchi method can be utilized.

Adaptive positive position feedback control with a feedforward compensator of a magnetostrictive beam for vibration suppression

NASA Astrophysics Data System (ADS)

Bian, Leixiang; Zhu, Wei

2018-07-01

In this paper, a Fe–Ga alloy magnetostrictive beam is designed as an actuator to restrain the vibration of a supported mass. Dynamic modeling of the system based on the transfer matrix method of multibody system is first shown, and then a hybrid controller is developed to achieve vibration control. The proposed vibration controller combines a multi-mode adaptive positive position feedback (APPF) with a feedforward compensator. In the APPF control, an adaptive natural frequency estimator based on the recursive least-square method is developed to be used. In the feedforward compensator, the hysteresis of the magnetostrictive beam is linearized based on a Bouc–Wen model. The further remarkable vibration suppression capability of the proposed hybrid controller is demonstrated experimentally and compared with the positive position feedback controller. Experiment results show that the proposed controller is applicable to the magnetostrictive beam for improving vibration control effectiveness.

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

NASA Technical Reports Server (NTRS)

Padgett, Mary L. (Editor)

1993-01-01

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

On advanced configuration enhance adaptive system optimization

NASA Astrophysics Data System (ADS)

Liu, Hua; Ding, Quanxin; Wang, Helong; Guo, Chunjie; Chen, Hongliang; Zhou, Liwei

2017-10-01

For aim to find an effective method to structure to enhance these adaptive system with some complex function and look forward to establish an universally applicable solution in prototype and optimization. As the most attractive component in adaptive system, wave front corrector is constrained by some conventional technique and components, such as polarization dependence and narrow working waveband. Advanced configuration based on a polarized beam split can optimized energy splitting method used to overcome these problems effective. With the global algorithm, the bandwidth has been amplified by more than five times as compared with that of traditional ones. Simulation results show that the system can meet the application requirements in MTF and other related criteria. Compared with the conventional design, the system has reduced in volume and weight significantly. Therefore, the determining factors are the prototype selection and the system configuration, Results show their effectiveness.

Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems.

PubMed

Ashtiani Haghighi, Donya; Mobayen, Saleh

2018-04-01

This paper proposes an adaptive super-twisting decoupled terminal sliding mode control technique for a class of fourth-order systems. The adaptive-tuning law eliminates the requirement of the knowledge about the upper bounds of external perturbations. Using the proposed control procedure, the state variables of cart-pole system are converged to decoupled terminal sliding surfaces and their equilibrium points in the finite time. Moreover, via the super-twisting algorithm, the chattering phenomenon is avoided without affecting the control performance. The numerical results demonstrate the high stabilization accuracy and lower performance indices values of the suggested method over the other ones. The simulation results on the cart-pole system as well as experimental validations demonstrate that the proposed control technique exhibits a reasonable performance in comparison with the other methods. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Kun, David William

Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external disturbances such as wind gusts and turbulence. This thesis develops the ARC-LMI attitude and position controllers for an X-configuration quadrotor helicopter. The inner-loop of the autopilot controls the attitude and altitude of the quadrotor, and the outer-loop controls its position in the earth-fixed coordinate frame. Furthermore, by intelligently generating a smooth trajectory from the given reference coordinates (waypoints), the transient performance is improved. The simulation results indicate that the ARC-LMI controller design is useful for a variety of quadrotor applications, including precise trajectory tracking, autonomous waypoint navigation in the presence of disturbances, and package delivery without loss of performance.

Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

PubMed Central

Antoniou, Miranta; Kolamunnage-Dona, Ruwanthi; Jorgensen, Andrea L.

2017-01-01

Biomarker-guided treatment is a rapidly developing area of medicine, where treatment choice is personalised according to one or more of an individual’s biomarker measurements. A number of biomarker-guided trial designs have been proposed in the past decade, including both adaptive and non-adaptive trial designs which test the effectiveness of a biomarker-guided approach to treatment with the aim of improving patient health. A better understanding of them is needed as challenges occur both in terms of trial design and analysis. We have undertaken a comprehensive literature review based on an in-depth search strategy with a view to providing the research community with clarity in definition, methodology and terminology of the various biomarker-guided trial designs (both adaptive and non-adaptive designs) from a total of 211 included papers. In the present paper, we focus on non-adaptive biomarker-guided trial designs for which we have identified five distinct main types mentioned in 100 papers. We have graphically displayed each non-adaptive trial design and provided an in-depth overview of their key characteristics. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. Our comprehensive review provides guidance for those designing biomarker-guided trials. PMID:28125057

ISTC projects devoted to improving laser beam quality

NASA Astrophysics Data System (ADS)

Malakhov, Yu. I.

2007-05-01

Short overview is done about the activity of ISTC in a direction concerned with improving powerful laser beam quality by means of nonlinear and linear adaptive optics methods. Completed projects #0591 and #1929 resulted in the development of a stimulated Brillouin scattering (SBS) phase conjugation mirror of superhigh fidelity employing the kinoform optical elements (rasters of small lenses) of new generation designed for pulsed or pulse-periodic lasers with nanosecond scale pulse duration. Project #2631 is devoted to development of an adaptive optical system for phase registration and correction of laser beams with wave front vortices. The principles of operation of conventional adaptive systems are based on the assumption that the phase is a smooth continuous function in space. Therefore the solution of the Project tasks will assume a new step in adaptive optics.

Flexible design in water and wastewater engineering--definitions, literature and decision guide.

PubMed

Spiller, Marc; Vreeburg, Jan H G; Leusbrock, Ingo; Zeeman, Grietje

2015-02-01

Urban water and wastewater systems face uncertain developments including technological progress, climate change and urban development. To ensure the sustainability of these systems under dynamic conditions it has been proposed that technologies and infrastructure should be flexible, adaptive and robust. However, in literature it is often unclear what these technologies and infrastructure are. Furthermore, the terms flexible, adaptive and robust are often used interchangeably, despite important differences. In this paper we will i) define the terminology, ii) provide an overview of the status of flexible infrastructure design alternatives for water and wastewater networks and treatment, and iii) develop guidelines for the selection of flexible design alternatives. Results indicate that, with the exception of Net Present Valuation methods, there is little research available on the design and evaluation of technologies that can enable flexibility. Flexible design alternatives reviewed include robust design, phased design, modular design, modular/component platform design and design for remanufacturing. As developments in the water sector are driven by slow variables (climate change, urban development), rather than market forces, it is suggested that phased design or component platform designs are suitable for responding to change, while robust design is an option when operations face highly dynamic variability. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Professional Development Program for Dental Medical Educators in Kuwait: Needs Assessment, Program Design and Formative Evaluation

ERIC Educational Resources Information Center

Alyaseen, Haneen

2017-01-01

New innovative methods of teaching and learning adopted from mainstream research and development in educational theory and practice are being adapted to serve the unique needs of the medical professions. The success of these methods requires careful planning and establishment of faculty development programs. The purpose of this study is to perform…

Rapid Dynamic Assessment of Expertise to Improve the Efficiency of Adaptive Elearning

ERIC Educational Resources Information Center

Kalyuga, Slava; Sweller, John

2005-01-01

In this article we suggest a method of evaluating learner expertise based on assessment of the content of working memory and the extent to which cognitive load has been reduced by knowledge retrieved from long-term memory. The method was tested in an experiment with an elementary algebra tutor using a yoked control design. In the learner-adapted…

A STUDY OF THE APPLICATION OF LABORATORY TRAINING METHODS TO PROGRAMS AT AIR UNIVERSITY (OCTOBER 1964-JULY 1965).

ERIC Educational Resources Information Center

BOYER, RONALD K.; AND OTHERS

THIS 1964-65 STUDY SOUGHT TO EXPLORE APPLICATIONS OF LABORATORY TRAINING TO AIR UNIVERSITY PROGRAMS, TO PREDICT PROBLEMS IN ADAPTING THE LABORATORY METHOD TO SUCH PROGRAMS, AND TO DETERMINE USEFUL MODIFICATIONS THAT MIGHT BE MADE IN TRAINING DESIGNS. A GROUP OF 25 AIR UNIVERSITY PERSONNEL REPRESENTING VARIOUS RANKS AND SCHOOLS ATTENDED AN…

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.

Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach.

PubMed

Kim, Woojae; Pitt, Mark A; Lu, Zhong-Lin; Myung, Jay I

2017-11-01

Experimentation is at the heart of scientific inquiry. In the behavioral and neural sciences, where only a limited number of observations can often be made, it is ideal to design an experiment that leads to the rapid accumulation of information about the phenomenon under study. Adaptive experimentation has the potential to accelerate scientific progress by maximizing inferential gain in such research settings. To date, most adaptive experiments have relied on myopic, one-step-ahead strategies in which the stimulus on each trial is selected to maximize inference on the next trial only. A lingering question in the field has been how much additional benefit would be gained by optimizing beyond the next trial. A range of technical challenges has prevented this important question from being addressed adequately. This study applies dynamic programming (DP), a technique applicable for such full-horizon, "global" optimization, to model-based perceptual threshold estimation, a domain that has been a major beneficiary of adaptive methods. The results provide insight into conditions that will benefit from optimizing beyond the next trial. Implications for the use of adaptive methods in cognitive science are discussed. Copyright © 2016 Cognitive Science Society, Inc.

Post-hoc simulation study to adopt a computerized adaptive testing (CAT) for a Korean Medical License Examination.

PubMed

Seo, Dong Gi; Choi, Jeongwook

2018-05-17

Computerized adaptive testing (CAT) has been adopted in license examinations due to a test efficiency and accuracy. Many research about CAT have been published to prove the efficiency and accuracy of measurement. This simulation study investigated scoring method and item selection methods to implement CAT in Korean medical license examination (KMLE). This study used post-hoc (real data) simulation design. The item bank used in this study was designed with all items in a 2017 KMLE. All CAT algorithms for this study were implemented by a 'catR' package in R program. In terms of accuracy, Rasch and 2parametric logistic (PL) model performed better than 3PL model. Modal a Posteriori (MAP) or Expected a Posterior (EAP) provided more accurate estimates than MLE and WLE. Furthermore Maximum posterior weighted information (MPWI) or Minimum expected posterior variance (MEPV) performed better than other item selection methods. In terms of efficiency, Rasch model was recommended to reduce test length. Simulation study should be performed under varied test conditions before adopting a live CAT. Based on a simulation study, specific scoring and item selection methods should be predetermined before implementing a live CAT.

Attractive manifold-based adaptive solar attitude control of satellites in elliptic orbits

NASA Astrophysics Data System (ADS)

Lee, Keum W.; Singh, Sahjendra N.

2011-01-01

The paper presents a novel noncertainty-equivalent adaptive (NCEA) control system for the pitch attitude control of satellites in elliptic orbits using solar radiation pressure (SRP). The satellite is equipped with two identical solar flaps to produce control moments. The adaptive law is based on the attractive manifold design using filtered signals for synthesis, which is a modification of the immersion and invariance (I&I) method. The control system has a modular controller-estimator structure and has separate tunable gains. A special feature of this NCEA law is that the trajectories of the satellite converge to a manifold in an extended state space, and the adaptive law recovers the performance of a deterministic controller. This recovery of performance cannot be obtained with certainty-equivalent adaptive (CEA) laws. Simulation results are presented which show that the NCEA law accomplishes precise attitude control of the satellite in an elliptic orbit, despite large parameter uncertainties.

Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.

PubMed

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

2017-06-01

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.

Modified Adaptive Control for Region 3 Operation in the Presence of Wind Turbine Structural Modes

NASA Technical Reports Server (NTRS)

Frost, Susan Alane; Balas, Mark J.; Wright, Alan D.

2010-01-01

Many challenges exist for the operation of wind turbines in an efficient manner that is reliable and avoids component fatigue and failure. Turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, possibly causing component fatigue and failure. Wind turbine manufacturers are highly motivated to reduce component fatigue and failure that can lead to loss of revenue due to turbine down time and maintenance costs. The trend in wind turbine design is toward larger, more flexible turbines that are ideally suited to adaptive control methods due to the complexity and expense required to create accurate models of their dynamic characteristics. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the excitation of structural modes in the wind turbine. The control objective is accomplished by collectively pitching the turbine blades. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. The adaptive controller will demonstrate the ability to regulate generator speed in Region 3, while accommodating gusts, and reducing the excitation of certain structural modes in the wind turbine.

INITIATORS AND TRIGGERING CONDITIONS FOR ADAPTIVE AUTOMATION IN ADVANCED SMALL MODULAR REACTORS

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

Katya L Le Blanc; Johanna h Oxstrand

It is anticipated that Advanced Small Modular Reactors (AdvSMRs) will employ high degrees of automation. High levels of automation can enhance system performance, but often at the cost of reduced human performance. Automation can lead to human out-of the loop issues, unbalanced workload, complacency, and other problems if it is not designed properly. Researchers have proposed adaptive automation (defined as dynamic or flexible allocation of functions) as a way to get the benefits of higher levels of automation without the human performance costs. Adaptive automation has the potential to balance operator workload and enhance operator situation awareness by allocating functionsmore » to the operators in a way that is sensitive to overall workload and capabilities at the time of operation. However, there still a number of questions regarding how to effectively design adaptive automation to achieve that potential. One of those questions is related to how to initiate (or trigger) a shift in automation in order to provide maximal sensitivity to operator needs without introducing undesirable consequences (such as unpredictable mode changes). Several triggering mechanisms for shifts in adaptive automation have been proposed including: operator initiated, critical events, performance-based, physiological measurement, model-based, and hybrid methods. As part of a larger project to develop design guidance for human-automation collaboration in AdvSMRs, researchers at Idaho National Laboratory have investigated the effectiveness and applicability of each of these triggering mechanisms in the context of AdvSMR. Researchers reviewed the empirical literature on adaptive automation and assessed each triggering mechanism based on the human-system performance consequences of employing that mechanism. Researchers also assessed the practicality and feasibility of using the mechanism in the context of an AdvSMR control room. Results indicate that there are tradeoffs associated with each mechanism, but that some are more applicable to the AdvSMR domain. The two mechanisms that consistently improve performance in laboratory studies are operator initiated adaptive automation based on hierarchical task delegation and the Electroencephalogram(EEG) –based measure of engagement. Current EEG methods are intrusive and require intensive analysis; therefore it is not recommended for an AdvSMR control rooms at this time. Researchers also discuss limitations in the existing empirical literature and make recommendations for further research.« less

Deep Space Network Antenna Monitoring Using Adaptive Time Series Methods and Hidden Markov Models

NASA Technical Reports Server (NTRS)

Smyth, Padhraic; Mellstrom, Jeff

1993-01-01

The Deep Space Network (DSN)(designed and operated by the Jet Propulsion Laboratory for the National Aeronautics and Space Administration (NASA) provides end-to-end telecommunication capabilities between earth and various interplanetary spacecraft throughout the solar system.

Examining the impact of differential cultural adaptation with Latina/o immigrants exposed to adapted parent training interventions

PubMed Central

Parra-Cardona, J. Rubén; Bybee, Deborah; Sullivan, Cris M.; Domenech Rodríguez, Melanie M.; Dates, Brian; Tams, Lisa; Bernal, Guillermo

2016-01-01

Objective There is a dearth of empirical studies aimed at examining the impact of differential cultural adaptation of evidence-based clinical and prevention interventions. This prevention study consisted of a randomized controlled trial aimed at comparing the impact of two differentially culturally adapted versions of the evidence-based parenting intervention known as Parent Management Training, the Oregon Model (PMTOR). Method The sample consisted of 103 Latina/o immigrant families (190 individual parents). Each family was allocated to one of three conditions: (a) a culturally adapted PMTO (CA), (b) culturally adapted and enhanced PMTO (CE), and (c) a wait-list control. Measurements were implemented at baseline (T1), treatment completion (T2) and 6-month follow up (T3). Results Multi-level growth modeling analyses indicated statistically significant improvements on parenting skills for fathers and mothers (main effect) at 6-month follow-up in both adapted interventions, when compared to the control condition. With regards to parent-reported child behaviors, child internalizing behaviors were significantly lower for both parents in the CE intervention (main effect), compared with control at 6-month follow-up. No main effect was found for child externalizing behaviors. However, a Parent x Condition effect was found indicating a significant reduction of child externalizing behaviors for CE fathers compared to CA and control fathers at posttest and 6-month follow-up. Conclusion Present findings indicate the value of differential cultural adaptation research designs and the importance of examining effects for both mothers and fathers, particularly when culturally-focused and gender variables are considered for intervention design and implementation. PMID:28045288

Co-production of knowledge: recipe for success in land-based climate change adaptation?

NASA Astrophysics Data System (ADS)

Coninx, Ingrid; Swart, Rob

2015-04-01

After multiple failures of scientists to trigger policymakers and other relevant actors to take action when communicating research findings, the request for co-production (or co-creation) of knowledge and stakeholder involvement in climate change adaptation efforts has rapidly increased over the past few years. In particular for land-based adaptation, on-the-ground action is often met by societal resistance towards solutions proposed by scientists, by a misfit of potential solutions with the local context, leading to misunderstanding and even rejection of scientific recommendations. A fully integrative co-creation process in which both scientists and practitioners discuss climate vulnerability and possible responses, exploring perspectives and designing adaptation measures based on their own knowledge, is expected to prevent the adaptation deadlock. The apparent conviction that co-creation processes result in successful adaptation, has not yet been unambiguously empirically demonstrated, but has resulted in co-creation being one of basic principles in many new research and policy programmes. But is co-creation that brings knowledge of scientists and practitioners together always the best recipe for success in climate change adaptation? Assessing a number of actual cases, the authors have serious doubts. The paper proposes additional considerations for adaptively managing the environment that should be taken into account in the design of participatory knowledge development in which climate scientists play a role. These include the nature of the problem at stake; the values, interests and perceptions of the actors involved; the methods used to build trust, strengthen alignment and develop reciprocal relationships among scientists and practitioners; and the concreteness of the co-creation output.

An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)

PubMed Central

2011-01-01

Background Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction. Methods A proposed method with anisotropic diffusion as pre-processing and a novel Bounded Area Elimination (BAE) post-processing algorithm to improve the algorithm of ossification site localization technique are designed with the intent of improving the adaptive segmentation result and the region-of interest (ROI) localization accuracy. Results The results are then evaluated by quantitative analysis and qualitative analysis using texture feature evaluation. The result indicates that the image homogeneity after anisotropic diffusion has improved averagely on each age group for 17.59%. Results of experiments showed that the smoothness has been improved averagely 35% after BAE algorithm and the improvement of ROI localization has improved for averagely 8.19%. The MSSIM has improved averagely 10.49% after performing the BAE algorithm on the adaptive segmented hand radiograph. Conclusions The result indicated that hand radiographs which have undergone anisotropic diffusion have greatly reduced the noise in the segmented image and the result as well indicated that the BAE algorithm proposed is capable of removing the artifacts generated in adaptive segmentation. PMID:21952080

An incremental database access method for autonomous interoperable databases

NASA Technical Reports Server (NTRS)

Roussopoulos, Nicholas; Sellis, Timos

1994-01-01

We investigated a number of design and performance issues of interoperable database management systems (DBMS's). The major results of our investigation were obtained in the areas of client-server database architectures for heterogeneous DBMS's, incremental computation models, buffer management techniques, and query optimization. We finished a prototype of an advanced client-server workstation-based DBMS which allows access to multiple heterogeneous commercial DBMS's. Experiments and simulations were then run to compare its performance with the standard client-server architectures. The focus of this research was on adaptive optimization methods of heterogeneous database systems. Adaptive buffer management accounts for the random and object-oriented access methods for which no known characterization of the access patterns exists. Adaptive query optimization means that value distributions and selectives, which play the most significant role in query plan evaluation, are continuously refined to reflect the actual values as opposed to static ones that are computed off-line. Query feedback is a concept that was first introduced to the literature by our group. We employed query feedback for both adaptive buffer management and for computing value distributions and selectivities. For adaptive buffer management, we use the page faults of prior executions to achieve more 'informed' management decisions. For the estimation of the distributions of the selectivities, we use curve-fitting techniques, such as least squares and splines, for regressing on these values.

Feasibility of adapting the fundamentals of laparoscopic surgery trainer box to endoscopic skills training tool.

PubMed

Crespin, Oscar M; Okrainec, Allan; Kwong, Andrea V; Habaz, Ilay; Jimenez, Maria Carolina; Szasz, Peter; Weiss, Ethan; Gonzalez, Cecilia G; Mosko, Jeffrey D; Liu, Louis W C; Swanstrom, Lee L; Perretta, Silvana; Shlomovitz, Eran

2018-06-01

The fundamentals of laparoscopic surgery (FLS) training box is a validated tool, already accessible to surgical trainees to hone their laparoscopic skills. We aim to investigate the feasibility of adapting the FLS box for the practice and assessment of endoscopic skills. This would allow for a highly available, reusable, low-cost, mechanical trainer. The design and development process was based on a user-centered design, which is a combination of the design thinking method and cognitive task analysis. The process comprises four phases: empathy, cognitive, prototyping/adaptation, and end user testing. The underlying idea was to utilize as many of the existing components of FLS training to maintain simplicity and cost effectiveness while allowing for the practice of clinically relevant endoscopic skills. A sample size of 18 participants was calculated to be sufficient to detect performance differences between experts and trainees using a two tailed t test with alpha set at 0.05, standard deviation of 5.5, and a power of 80%. Adaptation to the FLS box included two fundamental attachments: a front panel with an insertion point for an endoscope and a shaft which provides additional support and limits movement of the scope. The panel also allows for mounting of retroflexion tasks. Six endoscopic tasks inspired by FLS were designed (two of which utilize existing FLS components). Pilot testing with 38 participants showed high user's satisfaction and demonstrated that the trainer was robust and reliable. Task performance times was able to discriminate between trainees and experts for all six tasks. A mechanical, reusable, low-cost adaptation of the FLS training box for endoscopic skills is feasible and has high user satisfaction. Preliminary testing shows that the simulator is able to discriminate between trainees and experts. Following further validation, this adaptation may act as a supplement to the FES program.

The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

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

Barkana, Itzhak, E-mail: ibarkana@gmail.com

Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measuremore » of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.« less

Behavior Change Interventions to Improve the Health of Racial and Ethnic Minority Populations: A Tool Kit of Adaptation Approaches

PubMed Central

Davidson, Emma M; Liu, Jing Jing; Bhopal, Raj; White, Martin; Johnson, Mark RD; Netto, Gina; Wabnitz, Cecile; Sheikh, Aziz

2013-01-01

Context Adapting behavior change interventions to meet the needs of racial and ethnic minority populations has the potential to enhance their effectiveness in the target populations. But because there is little guidance on how best to undertake these adaptations, work in this field has proceeded without any firm foundations. In this article, we present our Tool Kit of Adaptation Approaches as a framework for policymakers, practitioners, and researchers interested in delivering behavior change interventions to ethnically diverse, underserved populations in the United Kingdom. Methods We undertook a mixed-method program of research on interventions for smoking cessation, increasing physical activity, and promoting healthy eating that had been adapted to improve salience and acceptability for African-, Chinese-, and South Asian–origin minority populations. This program included a systematic review (reported using PRISMA criteria), qualitative interviews, and a realist synthesis of data. Findings We compiled a richly informative data set of 161 publications and twenty-six interviews detailing the adaptation of behavior change interventions and the contexts in which they were undertaken. On the basis of these data, we developed our Tool Kit of Adaptation Approaches, which contains (1) a forty-six-item Typology of Adaptation Approaches; (2) a Pathway to Adaptation, which shows how to use the Typology to create a generic behavior change intervention; and (3) RESET, a decision tool that provides practical guidance on which adaptations to use in different contexts. Conclusions Our Tool Kit of Adaptation Approaches provides the first evidence-derived suite of materials to support the development, design, implementation, and reporting of health behavior change interventions for minority groups. The Tool Kit now needs prospective, empirical evaluation in a range of intervention and population settings. PMID:24320170

Adaptive marginal median filter for colour images.

PubMed

Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

2011-01-01

This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

The semantic connectivity map: an adapting self-organising knowledge discovery method in data bases. Experience in gastro-oesophageal reflux disease.

PubMed

Buscema, Massimo; Grossi, Enzo

2008-01-01

We describe here a new mapping method able to find out connectivity traces among variables thanks to an artificial adaptive system, the Auto Contractive Map (AutoCM), able to define the strength of the associations of each variable with all the others in a dataset. After the training phase, the weights matrix of the AutoCM represents the map of the main connections between the variables. The example of gastro-oesophageal reflux disease data base is extremely useful to figure out how this new approach can help to re-design the overall structure of factors related to complex and specific diseases description.

Learning from adaptive neural dynamic surface control of strict-feedback systems.

PubMed

Wang, Min; Wang, Cong

2015-06-01

Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

Anfis Approach for Sssc Controller Design for the Improvement of Transient Stability Performance

NASA Astrophysics Data System (ADS)

Khuntia, Swasti R.; Panda, Sidhartha

2011-06-01

In this paper, Adaptive Neuro-Fuzzy Inference System (ANFIS) method based on the Artificial Neural Network (ANN) is applied to design a Static Synchronous Series Compensator (SSSC)-based controller for improvement of transient stability. The proposed ANFIS controller combines the advantages of fuzzy controller and quick response and adaptability nature of ANN. The ANFIS structures were trained using the generated database by fuzzy controller of SSSC. It is observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances. The results prove that the proposed SSSC-based ANFIS controller is found to be robust to fault location and change in operating conditions. Further, the results obtained are compared with the conventional lead-lag controllers for SSSC.

Monitoring is not enough: on the need for a model-based approach to migratory bird management

USGS Publications Warehouse

Nichols, J.D.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Informed management requires information about system state and about effects of potential management actions on system state. Population monitoring can provide the needed information about system state, as well as information that can be used to investigate effects of management actions. Three methods for investigating effects of management on bird populations are (1) retrospective analysis, (2) formal experimentation and constrained-design studies, and (3) adaptive management. Retrospective analyses provide weak inferences, regardless of the quality of the monitoring data. The active use of monitoring data in experimental or constrained-design studies or in adaptive management is recommended. Under both approaches, learning occurs via the comparison of estimates from the monitoring program with predictions from competing management models.

Adaptive Modulation for DFIG and STATCOM With High-Voltage Direct Current Transmission.

PubMed

Tang, Yufei; He, Haibo; Ni, Zhen; Wen, Jinyu; Huang, Tingwen

2016-08-01

This paper develops an adaptive modulation approach for power system control based on the approximate/adaptive dynamic programming method, namely, the goal representation heuristic dynamic programming (GrHDP). In particular, we focus on the fault recovery problem of a doubly fed induction generator (DFIG)-based wind farm and a static synchronous compensator (STATCOM) with high-voltage direct current (HVDC) transmission. In this design, the online GrHDP-based controller provides three adaptive supplementary control signals to the DFIG controller, STATCOM controller, and HVDC rectifier controller, respectively. The mechanism is to observe the system states and their derivatives and then provides supplementary control to the plant according to the utility function. With the GrHDP design, the controller can adaptively develop an internal goal representation signal according to the observed power system states, therefore, to achieve more effective learning and modulating. Our control approach is validated on a wind power integrated benchmark system with two areas connected by HVDC transmission lines. Compared with the classical direct HDP and proportional integral control, our GrHDP approach demonstrates the improved transient stability under system faults. Moreover, experiments under different system operating conditions with signal transmission delays are also carried out to further verify the effectiveness and robustness of the proposed approach.

M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2015-01-01

The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.

A temperature control design for a tapered element oscillating microbalance sensing surface

NASA Technical Reports Server (NTRS)

1982-01-01

A design study is presented which shows that a tapered element oscillating microbalance can be adapted for temperature control under space application by mating with multistage thermoelectric coolers in such a way that an integral structure evolves. The control of the temperature of the sensing surface can be achieved in a number of ways. An indirect method which uses a measurement of the absorbed power is recommended. The design goals can be met if a relaxation of the power requirement can be considered.

Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

The paper presents a certainty equivalence state feedback indirect adaptive control design method for the systems of any relative degree with unmatched uncertainties. The approach is based on the parameter identification (estimation) model, which is completely separated from the control design and is capable of producing parameter estimates as fast as the computing power allows without generating high frequency oscillations. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters.

Using Direct Policy Search to Identify Robust Strategies in Adapting to Uncertain Sea Level Rise and Storm Surge

NASA Astrophysics Data System (ADS)

Garner, G. G.; Keller, K.

2017-12-01

Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with deeply uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods have provided tremendous insight into this decision problem, but are often silent on tradeoffs as well as the effects of tail-area events and of potential future learning. Here we reformulate a simple sea-level rise adaptation model to address these concerns. We show that Direct Policy Search yields improved solution quality, with respect to Pareto-dominance in the objectives, over the traditional approach under uncertain sea-level rise projections and storm surge. Additionally, the new formulation produces high quality solutions with less computational demands than the traditional approach. Our results illustrate the utility of multi-objective adaptive formulations for the example of coastal adaptation, the value of information provided by observations, and point to wider-ranging application in climate change adaptation decision problems.

Adaptive laboratory evolution -- principles and applications for biotechnology.

PubMed

Dragosits, Martin; Mattanovich, Diethard

2013-07-01

Adaptive laboratory evolution is a frequent method in biological studies to gain insights into the basic mechanisms of molecular evolution and adaptive changes that accumulate in microbial populations during long term selection under specified growth conditions. Although regularly performed for more than 25 years, the advent of transcript and cheap next-generation sequencing technologies has resulted in many recent studies, which successfully applied this technique in order to engineer microbial cells for biotechnological applications. Adaptive laboratory evolution has some major benefits as compared with classical genetic engineering but also some inherent limitations. However, recent studies show how some of the limitations may be overcome in order to successfully incorporate adaptive laboratory evolution in microbial cell factory design. Over the last two decades important insights into nutrient and stress metabolism of relevant model species were acquired, whereas some other aspects such as niche-specific differences of non-conventional cell factories are not completely understood. Altogether the current status and its future perspectives highlight the importance and potential of adaptive laboratory evolution as approach in biotechnological engineering.

Adjustable Trajectory Design Based on Node Density for Mobile Sink in WSNs

PubMed Central

Yang, Guisong; Liu, Shuai; He, Xingyu; Xiong, Naixue; Wu, Chunxue

2016-01-01

The design of movement trajectories for mobile sink plays an important role in data gathering for Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, as well as the network lifetime. In some scenarios, the whole network can be divided into subareas where the nodes are randomly deployed. The node densities of these subareas are quite different, which may result in a decreased packet delivery ratio and network lifetime if the movement trajectory of the mobile sink cannot adapt to these differences. To address these problems, we propose an adjustable trajectory design method based on node density for mobile sink in WSNs. The movement trajectory of the mobile sink in each subarea follows the Hilbert space-filling curve. Firstly, the trajectory is constructed based on network size. Secondly, the adjustable trajectory is established based on node density in specific subareas. Finally, the trajectories in each subarea are combined to acquire the whole network’s movement trajectory for the mobile sink. In addition, an adaptable power control scheme is designed to adjust nodes’ transmitting range dynamically according to the movement trajectory of the mobile sink in each subarea. The simulation results demonstrate that the proposed trajectories can adapt to network changes flexibly, thus outperform both in packet delivery ratio and in energy consumption the trajectories designed only based on the network size and the whole network node density. PMID:27941662

Coupling Adaptation Tipping Points and Engineering Options: New Insights for Resilient Water Infrastructure Replacement Planning

NASA Astrophysics Data System (ADS)

Smet, K.; de Neufville, R.; van der Vlist, M.

2017-12-01

This work presents an innovative approach for replacement planning for aging water infrastructure given uncertain future conditions. We draw upon two existing methodologies to develop an integrated long-term replacement planning framework. We first expand the concept of Adaptation Tipping Points to generate long-term planning timelines that incorporate drivers of investment related to both internal structural processes as well as changes in external operating conditions. Then, we use Engineering Options to explore different actions taken at key moments in this timeline. Contrasting to the traditionally more static approach to infrastructure design, designing the next generation of infrastructure so it can be changed incrementally is a promising method to safeguard current investments given future uncertainty. This up-front inclusion of structural options in the system actively facilitates future adaptation, transforming uncertainty management in infrastructure planning from reactive to more proactive. A two-part model underpins this approach. A simulation model generates diverse future conditions, allowing development of timelines of intervention moments in the structure's life. This feeds into an economic model, evaluating the lifetime performance of different replacement strategies, making explicit the value of different designs and their flexibility. A proof of concept study demonstrates this approach for a pumping station. The strategic planning timelines for this structure demonstrate that moments when capital interventions become necessary due to reduced functionality from structural degradation or changed operating conditions are widely spread over the structure's life. The disparate timing of these necessary interventions supports an incremental, adaptive mindset when considering end-of-life and replacement decisions. The analysis then explores different replacement decisions, varying the size and specific options included in the proposed new structure. Results show that incremental adaptive designs and incorporating options can improve economic performance, as compared to traditional, "build it once & build it big" designs. The benefit from incorporating flexibility varies with structural functionality, future conditions and the specific options examined.

ADGS-2100 Adaptive Display and Guidance System Window Manager Analysis

NASA Technical Reports Server (NTRS)

Whalen, Mike W.; Innis, John D.; Miller, Steven P.; Wagner, Lucas G.

2006-01-01

Recent advances in modeling languages have made it feasible to formally specify and analyze the behavior of large system components. Synchronous data flow languages, such as Lustre, SCR, and RSML-e are particularly well suited to this task, and commercial versions of these tools such as SCADE and Simulink are growing in popularity among designers of safety critical systems, largely due to their ability to automatically generate code from the models. At the same time, advances in formal analysis tools have made it practical to formally verify important properties of these models to ensure that design defects are identified and corrected early in the lifecycle. This report describes how these tools have been applied to the ADGS-2100 Adaptive Display and Guidance Window Manager being developed by Rockwell Collins Inc. This work demonstrates how formal methods can be easily and cost-efficiently used to remove defects early in the design cycle.

Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems.

PubMed

Peng, Zhouhua; Wang, Dan; Zhang, Hongwei; Sun, Gang

2014-08-01

This paper addresses the leader-follower synchronization problem of uncertain dynamical multiagent systems with nonlinear dynamics. Distributed adaptive synchronization controllers are proposed based on the state information of neighboring agents. The control design is developed for both undirected and directed communication topologies without requiring the accurate model of each agent. This result is further extended to the output feedback case where a neighborhood observer is proposed based on relative output information of neighboring agents. Then, distributed observer-based synchronization controllers are derived and a parameter-dependent Riccati inequality is employed to prove the stability. This design has a favorable decouple property between the observer and the controller designs for nonlinear multiagent systems. For both cases, the developed controllers guarantee that the state of each agent synchronizes to that of the leader with bounded residual errors. Two illustrative examples validate the efficacy of the proposed methods.

Probabilistic DHP adaptive critic for nonlinear stochastic control systems.

PubMed

Herzallah, Randa

2013-06-01

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Káarnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

Support of surgical process modeling by using adaptable software user interfaces

NASA Astrophysics Data System (ADS)

Neumuth, T.; Kaschek, B.; Czygan, M.; Goldstein, D.; Strauß, G.; Meixensberger, J.; Burgert, O.

2010-03-01

Surgical Process Modeling (SPM) is a powerful method for acquiring data about the evolution of surgical procedures. Surgical Process Models are used in a variety of use cases including evaluation studies, requirements analysis and procedure optimization, surgical education, and workflow management scheme design. This work proposes the use of adaptive, situation-aware user interfaces for observation support software for SPM. We developed a method to support the modeling of the observer by using an ontological knowledge base. This is used to drive the graphical user interface for the observer to restrict the search space of terminology depending on the current situation. In the evaluation study it is shown, that the workload of the observer was decreased significantly by using adaptive user interfaces. 54 SPM observation protocols were analyzed by using the NASA Task Load Index and it was shown that the use of the adaptive user interface disburdens the observer significantly in workload criteria effort, mental demand and temporal demand, helping him to concentrate on his essential task of modeling the Surgical Process.

Adaptive adjustment of the randomization ratio using historical control data

PubMed Central

Hobbs, Brian P.; Carlin, Bradley P.; Sargent, Daniel J.

2013-01-01

Background Prospective trial design often occurs in the presence of “acceptable” [1] historical control data. Typically this data is only utilized for treatment comparison in a posteriori retrospective analysis to estimate population-averaged effects in a random-effects meta-analysis. Purpose We propose and investigate an adaptive trial design in the context of an actual randomized controlled colorectal cancer trial. This trial, originally reported by Goldberg et al. [2], succeeded a similar trial reported by Saltz et al. [3], and used a control therapy identical to that tested (and found beneficial) in the Saltz trial. Methods The proposed trial implements an adaptive randomization procedure for allocating patients aimed at balancing total information (concurrent and historical) among the study arms. This is accomplished by assigning more patients to receive the novel therapy in the absence of strong evidence for heterogeneity among the concurrent and historical controls. Allocation probabilities adapt as a function of the effective historical sample size (EHSS) characterizing relative informativeness defined in the context of a piecewise exponential model for evaluating time to disease progression. Commensurate priors [4] are utilized to assess historical and concurrent heterogeneity at interim analyses and to borrow strength from the historical data in the final analysis. The adaptive trial’s frequentist properties are simulated using the actual patient-level historical control data from the Saltz trial and the actual enrollment dates for patients enrolled into the Goldberg trial. Results Assessing concurrent and historical heterogeneity at interim analyses and balancing total information with the adaptive randomization procedure leads to trials that on average assign more new patients to the novel treatment when the historical controls are unbiased or slightly biased compared to the concurrent controls. Large magnitudes of bias lead to approximately equal allocation of patients among the treatment arms. Using the proposed commensurate prior model to borrow strength from the historical data, after balancing total information with the adaptive randomization procedure, provides admissible estimators of the novel treatment effect with desirable bias-variance trade-offs. Limitations Adaptive randomization methods in general are sensitive to population drift and more suitable for trials that initiate with gradual enrollment. Balancing information among study arms in time-to-event analyses is difficult in the presence of informative right-censoring. Conclusions The proposed design could prove important in trials that follow recent evaluations of a control therapy. Efficient use of the historical controls is especially important in contexts where reliance on pre-existing information is unavoidable because the control therapy is exceptionally hazardous, expensive, or the disease is rare. PMID:23690095

Blading Design for Axial Turbomachines

DTIC Science & Technology

1989-05-01

three- dimensional, viscous computation systems appear to have a long development period ahead, in which fluid shear stress modeling and computation time ...and n directions and T is the shear stress , As a consequence the solution time is longer than for integral methods, dependent largely on thc accuracy of...distributions over airfoils is an adaptation of thin plate deflection theory from stress analysis. At the same time , it minimizes designer effort

Assessment and Evaluation in Adapted Physical Education.

ERIC Educational Resources Information Center

Kennedy, Charlotte I.; Bundschuh, Ernie

Intended for physical education teachers, the booklet describes informal and formal methods for evaluating handicapped children to determine whether they can participate in a regular physical education program with nonhandicapped students, in a regular physical education program with modification, or in a specially designed physical education…

Teacher Resource Guide, Project ECO.

ERIC Educational Resources Information Center

Ames Public Schools, IA.

More than 100 outdoor education and field science projects are compiled in this teacher's resource book. Designed for use in grades K-9, the activities cover the areas of field taxonomy, laboratory taxonomy, autecology, synecology, adaptation, economic biology, conservation, museum methods, culturing, zoo keeping, gardening, and woodcraft. Each…

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

PubMed

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

2015-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Real-time WebRTC-based design for a telepresence wheelchair.

PubMed

Van Kha Ly Ha; Rifai Chai; Nguyen, Hung T

2017-07-01

This paper presents a novel approach to the telepresence wheelchair system which is capable of real-time video communication and remote interaction. The investigation of this emerging technology aims at providing a low-cost and efficient way for assisted-living of people with disabilities. The proposed system has been designed and developed by deploying the JavaScript with Hyper Text Markup Language 5 (HTML5) and Web Real-time Communication (WebRTC) in which the adaptive rate control algorithm for video transmission is invoked. We conducted experiments in real-world environments, and the wheelchair was controlled from a distance using the Internet browser to compare with existing methods. The results show that the adaptively encoded video streaming rate matches the available bandwidth. The video streaming is high-quality with approximately 30 frames per second (fps) and round trip time less than 20 milliseconds (ms). These performance results confirm that the WebRTC approach is a potential method for developing a telepresence wheelchair system.

Switching Reinforcement Learning for Continuous Action Space

NASA Astrophysics Data System (ADS)

Nagayoshi, Masato; Murao, Hajime; Tamaki, Hisashi

Reinforcement Learning (RL) attracts much attention as a technique of realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL into practical use. This difficulty includes a problem of designing a suitable action space of an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, we propose switching RL model to mimic a process of an infant's motor development in which gross motor skills develop before fine motor skills. Then, a method for switching controllers is constructed by introducing and referring to the “entropy”. Further, through computational experiments by using robot navigation problems with one and two-dimensional continuous action space, the validity of the proposed method has been confirmed.

A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2013-11-07

Protein-Protein interaction (PPI) is one of the most important data in understanding the cellular processes. Many interesting methods have been proposed in order to predict PPIs. However, the methods which are based on the sequence of proteins as a prior knowledge are more universal. In this paper, a sequence-based, fast, and adaptive PPI prediction method is introduced to assign two proteins to an interaction class (yes, no). First, in order to improve the presentation of the sequences, twelve physicochemical properties of amino acid have been used by different representation methods to transform the sequence of protein pairs into different feature vectors. Then, for speeding up the learning process and reducing the effect of noise PPI data, principal component analysis (PCA) is carried out as a proper feature extraction algorithm. Finally, a new and adaptive Learning Vector Quantization (LVQ) predictor is designed to deal with different models of datasets that are classified into balanced and imbalanced datasets. The accuracy of 93.88%, 90.03%, and 89.72% has been found on S. cerevisiae, H. pylori, and independent datasets, respectively. The results of various experiments indicate the efficiency and validity of the method. © 2013 Published by Elsevier Ltd.

A Generalized Framework for Constrained Design Optimization of General Supersonic Configurations Using Adjoint Based Sensitivity Derivatives

NASA Technical Reports Server (NTRS)

Karman, Steve L., Jr.

2011-01-01

The Aeronautics Research Mission Directorate (ARMD) sent out an NASA Research Announcement (NRA) for proposals soliciting research and technical development. The proposed research program was aimed at addressing the desired milestones and outcomes of ROA (ROA-2006) Subtopic A.4.1.1 Advanced Computational Methods. The second milestone, SUP.1.06.02 Robust, validated mesh adaptation and error quantification for near field Computational Fluid Dynamics (CFD), was addressed by the proposed research. Additional research utilizing the direct links to geometry through a CAD interface enabled by this work will allow for geometric constraints to be applied and address the final milestone, SUP2.07.06 Constrained low-drag supersonic aerodynamic design capability. The original product of the proposed research program was an integrated system of tools that can be used for the mesh mechanics required for rapid high fidelity analysis and for design of supersonic cruise vehicles. These Euler and Navier-Stokes volume grid manipulation tools were proposed to efficiently use parallel processing. The mesh adaptation provides a systematic approach for achieving demonstrated levels of accuracy in the solutions. NASA chose to fund only the mesh generation/adaptation portion of the proposal. So this report describes the completion of the proposed tasks for mesh creation, manipulation and adaptation as it pertains to sonic boom prediction of supersonic configurations.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Putting the brain to work: neuroergonomics past, present, and future.

PubMed

Parasuraman, Raja; Wilson, Glenn F

2008-06-01

The authors describe research and applications in prominent areas of neuroergonomics. Because human factors/ergonomics examines behavior and mind at work, it should include the study of brain mechanisms underlying human performance. Neuroergonomic studies are reviewed in four areas: workload and vigilance, adaptive automation, neuroengineering, and molecular genetics and individual differences. Neuroimaging studies have helped identify the components of mental workload, workload assessment in complex tasks, and resource depletion in vigilance. Furthermore, real-time neurocognitive assessment of workload can trigger adaptive automation. Neural measures can also drive brain-computer interfaces to provide disabled users new communication channels. Finally, variants of particular genes can be associated with individual differences in specific cognitive functions. Neuroergonomics shows that considering what makes work possible - the human brain - can enrich understanding of the use of technology by humans and can inform technological design. Applications of neuroergonomics include the assessment of operator workload and vigilance, implementation of real-time adaptive automation, neuroengineering for people with disabilities, and design of selection and training methods.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE PAGES

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; ...

2017-12-27

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

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

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

Field Guide for Designing Human Interaction with Intelligent Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Thronesbery, Carroll G.

1998-01-01

The characteristics of this Field Guide approach address the problems of designing innovative software to support user tasks. The requirements for novel software are difficult to specify a priori, because there is not sufficient understanding of how the users' tasks should be supported, and there are not obvious pre-existing design solutions. When the design team is in unfamiliar territory, care must be taken to avoid rushing into detailed design, requirements specification, or implementation of the wrong product. The challenge is to get the right design and requirements in an efficient, cost-effective manner. This document's purpose is to describe the methods we are using to design human interactions with intelligent systems which support Space Shuttle flight controllers in the Mission Control Center at NASA/Johnson Space Center. Although these software systems usually have some intelligent features, the design challenges arise primarily from the innovation needed in the software design. While these methods are tailored to our specific context, they should be extensible, and helpful to designers of human interaction with other types of automated systems. We review the unique features of this context so that you can determine how to apply these methods to your project Throughout this Field Guide, goals of the design methods are discussed. This should help designers understand how a specific method might need to be adapted to the project at hand.

Implementation of a flexible and scalable particle-in-cell method for massively parallel computations in the mantle convection code ASPECT

NASA Astrophysics Data System (ADS)

Gassmöller, Rene; Bangerth, Wolfgang

2016-04-01

Particle-in-cell methods have a long history and many applications in geodynamic modelling of mantle convection, lithospheric deformation and crustal dynamics. They are primarily used to track material information, the strain a material has undergone, the pressure-temperature history a certain material region has experienced, or the amount of volatiles or partial melt present in a region. However, their efficient parallel implementation - in particular combined with adaptive finite-element meshes - is complicated due to the complex communication patterns and frequent reassignment of particles to cells. Consequently, many current scientific software packages accomplish this efficient implementation by specifically designing particle methods for a single purpose, like the advection of scalar material properties that do not evolve over time (e.g., for chemical heterogeneities). Design choices for particle integration, data storage, and parallel communication are then optimized for this single purpose, making the code relatively rigid to changing requirements. Here, we present the implementation of a flexible, scalable and efficient particle-in-cell method for massively parallel finite-element codes with adaptively changing meshes. Using a modular plugin structure, we allow maximum flexibility of the generation of particles, the carried tracer properties, the advection and output algorithms, and the projection of properties to the finite-element mesh. We present scaling tests ranging up to tens of thousands of cores and tens of billions of particles. Additionally, we discuss efficient load-balancing strategies for particles in adaptive meshes with their strengths and weaknesses, local particle-transfer between parallel subdomains utilizing existing communication patterns from the finite element mesh, and the use of established parallel output algorithms like the HDF5 library. Finally, we show some relevant particle application cases, compare our implementation to a modern advection-field approach, and demonstrate under which conditions which method is more efficient. We implemented the presented methods in ASPECT (aspect.dealii.org), a freely available open-source community code for geodynamic simulations. The structure of the particle code is highly modular, and segregated from the PDE solver, and can thus be easily transferred to other programs, or adapted for various application cases.

From user needs to system specifications: multi-disciplinary thematic seminars as a collaborative design method for development of health information systems.

PubMed

Scandurra, I; Hägglund, M; Koch, S

2008-08-01

This paper presents a new multi-disciplinary method for user needs analysis and requirements specification in the context of health information systems based on established theories from the fields of participatory design and computer supported cooperative work (CSCW). Whereas conventional methods imply a separate, sequential needs analysis for each profession, the "multi-disciplinary thematic seminar" (MdTS) method uses a collaborative design process. Application of the method in elderly homecare resulted in prototypes that were well adapted to the intended user groups. Vital information in the points of intersection between different care professions was elicited and a holistic view of the entire care process was obtained. Health informatics-usability specialists and clinical domain experts are necessary to apply the method. Although user needs acquisition can be time-consuming, MdTS was perceived to efficiently identify in-context user needs, and transformed these directly into requirements specifications. Consequently the method was perceived to expedite the entire ICT implementation process.

Valuation of design adaptability in aerospace systems

NASA Astrophysics Data System (ADS)

Fernandez Martin, Ismael

As more information is brought into early stages of the design, more pressure is put on engineers to produce a reliable, high quality, and financially sustainable product. Unfortunately, requirements established at the beginning of a new project by customers, and the environment that surrounds them, continue to change in some unpredictable ways. The risk of designing a system that may become obsolete during early stages of production is currently tackled by the use of robust design simulation, a method that allows to simultaneously explore a plethora of design alternatives and requirements with the intention of accounting for uncertain factors in the future. Whereas this design technique has proven to be quite an improvement in design methods, under certain conditions, it fails to account for the change of uncertainty over time and the intrinsic value embedded in the system when certain design features are activated. This thesis introduces the concepts of adaptability and real options to manage risk foreseen in the face of uncertainty at early design stages. The method described herein allows decision-makers to foresee the financial impact of their decisions at the design level, as well as the final exposure to risk. In this thesis, cash flow models, traditionally used to obtain the forecast of a project's value over the years, were replaced with surrogate models that are capable of showing fluctuations on value every few days. This allowed a better implementation of real options valuation, optimization, and strategy selection. Through the option analysis model, an optimization exercise allows the user to obtain the best implementation strategy in the face of uncertainty as well as the overall value of the design feature. Here implementation strategy refers to the decision to include a new design feature in the system, after the design has been finalized, but before the end of its production life. The ability to do this in a cost efficient manner after the system design is under production is referred to as adaptability. This thesis contains two relevant examples regarding the decision of introducing new technologies. First, the case study of Southwest Airlines, and the decision it took to retrofit blended winglets technology in its already delivered Boeing 737-700, is introduced as a validation exercise and for calibration purposes. Such case also demonstrates that the method is applicable to a real life example with simple technologies. The second example analyzes the decision of introducing new technologies into the design of the new jet engine to power the next generation of narrow body aircraft. The development of such aircraft, set to replace the Boeing 737 and Airbus 320 models, is currently at conceptual levels. In this case, the manufacturer evaluates whether technologies should be included in the design, left out, or offered as an option to retrofit in the future. This case demonstrates the benefits of each of these actions and the monetary value of offering retrofitting options as upgrades to the airlines when the value of the technology fluctuates considerably between profitable and not profitable. The purpose of this case is to demonstrate the applicability of the method to the preliminary design phases of complex systems while accounting for uncertainty of external factors over time.

An adaptive image sparse reconstruction method combined with nonlocal similarity and cosparsity for mixed Gaussian-Poisson noise removal

NASA Astrophysics Data System (ADS)

Chen, Yong-fei; Gao, Hong-xia; Wu, Zi-ling; Kang, Hui

2018-01-01

Compressed sensing (CS) has achieved great success in single noise removal. However, it cannot restore the images contaminated with mixed noise efficiently. This paper introduces nonlocal similarity and cosparsity inspired by compressed sensing to overcome the difficulties in mixed noise removal, in which nonlocal similarity explores the signal sparsity from similar patches, and cosparsity assumes that the signal is sparse after a possibly redundant transform. Meanwhile, an adaptive scheme is designed to keep the balance between mixed noise removal and detail preservation based on local variance. Finally, IRLSM and RACoSaMP are adopted to solve the objective function. Experimental results demonstrate that the proposed method is superior to conventional CS methods, like K-SVD and state-of-art method nonlocally centralized sparse representation (NCSR), in terms of both visual results and quantitative measures.

Application of mixed-methods design in community-engaged research: Lessons learned from an evidence-based intervention for Latinos with chronic illness and minor depression.

PubMed

Aguado Loi, Claudia X; Alfonso, Moya L; Chan, Isabella; Anderson, Kelsey; Tyson, Dinorah Dina Martinez; Gonzales, Junius; Corvin, Jaime

2017-08-01

The purpose of this paper is to share lessons learned from a collaborative, community-informed mixed-methods approach to adapting an evidence-based intervention to meet the needs of Latinos with chronic disease and minor depression and their family members. Mixed-methods informed by community-based participatory research (CBPR) were employed to triangulate multiple stakeholders' perceptions of facilitators and barriers of implementing the adapted intervention in community settings. Community partners provided an insider perspective to overcome methodological challenges. The study's community informed mixed-methods: research approach offered advantages to a single research methodology by expanding or confirming research findings and engaging multiple stakeholders in data collection. This approach also allowed community partners to collaborate with academic partners in key research decisions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Designing Adaptive Low-Dissipative High Order Schemes for Long-Time Integrations. Chapter 1

NASA Technical Reports Server (NTRS)

Yee, Helen C.; Sjoegreen, B.; Mansour, Nagi N. (Technical Monitor)

2001-01-01

A general framework for the design of adaptive low-dissipative high order schemes is presented. It encompasses a rather complete treatment of the numerical approach based on four integrated design criteria: (1) For stability considerations, condition the governing equations before the application of the appropriate numerical scheme whenever it is possible; (2) For consistency, compatible schemes that possess stability properties, including physical and numerical boundary condition treatments, similar to those of the discrete analogue of the continuum are preferred; (3) For the minimization of numerical dissipation contamination, efficient and adaptive numerical dissipation control to further improve nonlinear stability and accuracy should be used; and (4) For practical considerations, the numerical approach should be efficient and applicable to general geometries, and an efficient and reliable dynamic grid adaptation should be used if necessary. These design criteria are, in general, very useful to a wide spectrum of flow simulations. However, the demand on the overall numerical approach for nonlinear stability and accuracy is much more stringent for long-time integration of complex multiscale viscous shock/shear/turbulence/acoustics interactions and numerical combustion. Robust classical numerical methods for less complex flow physics are not suitable or practical for such applications. The present approach is designed expressly to address such flow problems, especially unsteady flows. The minimization of employing very fine grids to overcome the production of spurious numerical solutions and/or instability due to under-resolved grids is also sought. The incremental studies to illustrate the performance of the approach are summarized. Extensive testing and full implementation of the approach is forthcoming. The results shown so far are very encouraging.

Model-free adaptive sliding mode controller design for generalized projective synchronization of the fractional-order chaotic system via radial basis function neural networks

NASA Astrophysics Data System (ADS)

Wang, L. M.

2017-09-01

A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master-slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown slave system (including the external disturbances). Consequently, based on the slide mode technology and the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized projective synchronization error. The main contribution of this paper is that a control strategy is provided for the generalized projective synchronization between two entirely unknown fractional-order chaotic systems subject to the unknown external disturbances, and the proposed control strategy only requires that the master system has the same fractional orders as the slave system. Moreover, the proposed method allows us to achieve all kinds of generalized projective chaos synchronizations by turning the user-defined parameters onto the desired values. Simulation results show the effectiveness of the proposed method and the robustness of the controlled system.

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.

RNAblueprint: flexible multiple target nucleic acid sequence design.

PubMed

Hammer, Stefan; Tschiatschek, Birgit; Flamm, Christoph; Hofacker, Ivo L; Findeiß, Sven

2017-09-15

Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility. We developed a C ++  library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages. RNAblueprint , Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA . s.hammer@univie.ac.at, ivo@tbi.univie.ac.at or sven@tbi.univie.ac.at. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.