Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

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

Anticipatory control: A software retrofit for current plant controllers

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

Parthasarathy, S.; Parlos, A.G.; Atiya, A.F.

1993-01-01

The design and simulated testing of an artificial neural network (ANN)-based self-adapting controller for complex process systems are presented in this paper. The proposed controller employs concepts based on anticipatory systems, which have been widely used in the petroleum and chemical industries, and they are slowly finding their way into the power industry. In particular, model predictive control (MPC) is used for the systematic adaptation of the controller parameters to achieve desirable plant performance over the entire operating envelope. The versatile anticipatory control algorithm developed in this study is projected to enhance plant performance and lend robustness to drifts inmore » plant parameters and to modeling uncertainties. This novel technique of integrating recurrent ANNs with a conventional controller structure appears capable of controlling complex, nonlinear, and nonminimum phase process systems. The direct, on-line adaptive control algorithm presented in this paper considers the plant response over a finite time horizon, diminishing the need for manual control or process interruption for controller gain tuning.« less

Design and implementation of adaptive PI control schemes for web tension control in roll-to-roll (R2R) manufacturing.

PubMed

Raul, Pramod R; Pagilla, Prabhakar R

2015-05-01

In this paper, two adaptive Proportional-Integral (PI) control schemes are designed and discussed for control of web tension in Roll-to-Roll (R2R) manufacturing systems. R2R systems are used to transport continuous materials (called webs) on rollers from the unwind roll to the rewind roll. Maintaining web tension at the desired value is critical to many R2R processes such as printing, coating, lamination, etc. Existing fixed gain PI tension control schemes currently used in industrial practice require extensive tuning and do not provide the desired performance for changing operating conditions and material properties. The first adaptive PI scheme utilizes the model reference approach where the controller gains are estimated based on matching of the actual closed-loop tension control systems with an appropriately chosen reference model. The second adaptive PI scheme utilizes the indirect adaptive control approach together with relay feedback technique to automatically initialize the adaptive PI gains. These adaptive tension control schemes can be implemented on any R2R manufacturing system. The key features of the two adaptive schemes is that their designs are simple for practicing engineers, easy to implement in real-time, and automate the tuning process. Extensive experiments are conducted on a large experimental R2R machine which mimics many features of an industrial R2R machine. These experiments include trials with two different polymer webs and a variety of operating conditions. Implementation guidelines are provided for both adaptive schemes. Experimental results comparing the two adaptive schemes and a fixed gain PI tension control scheme used in industrial practice are provided and discussed. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Model-free adaptive control of supercritical circulating fluidized-bed boilers

DOEpatents

Cheng, George Shu-Xing; Mulkey, Steven L

2014-12-16

A novel 3-Input-3-Output (3.times.3) Fuel-Air Ratio Model-Free Adaptive (MFA) controller is introduced, which can effectively control key process variables including Bed Temperature, Excess O2, and Furnace Negative Pressure of combustion processes of advanced boilers. A novel 7-input-7-output (7.times.7) MFA control system is also described for controlling a combined 3-Input-3-Output (3.times.3) process of Boiler-Turbine-Generator (BTG) units and a 5.times.5 CFB combustion process of advanced boilers. Those boilers include Circulating Fluidized-Bed (CFB) Boilers and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

Effortful Control and Adaptive Functioning of Homeless Children: Variable-Focused and Person-Focused Analyses

ERIC Educational Resources Information Center

Obradovic, Jelena

2010-01-01

Homeless children show significant developmental delays across major domains of adaptation, yet research on protective processes that may contribute to resilient adaptation in this highly disadvantaged group of children is extremely rare. This study examined the role of effortful control for adaption in 58 homeless children, ages 5-6, during their…

Switches of stimulus tagging frequencies interact with the conflict-driven control of selective attention, but not with inhibitory control.

PubMed

Scherbaum, Stefan; Frisch, Simon; Dshemuchadse, Maja

2016-01-01

Selective attention and its adaptation by cognitive control processes are considered a core aspect of goal-directed action. Often, selective attention is studied behaviorally with conflict tasks, but an emerging neuroscientific method for the study of selective attention is EEG frequency tagging. It applies different flicker frequencies to the stimuli of interest eliciting steady state visual evoked potentials (SSVEPs) in the EEG. These oscillating SSVEPs in the EEG allow tracing the allocation of selective attention to each tagged stimulus continuously over time. The present behavioral investigation points to an important caveat of using tagging frequencies: The flicker of stimuli not only produces a useful neuroscientific marker of selective attention, but interacts with the adaptation of selective attention itself. Our results indicate that RT patterns of adaptation after response conflict (so-called conflict adaptation) are reversed when flicker frequencies switch at once. However, this effect of frequency switches is specific to the adaptation by conflict-driven control processes, since we find no effects of frequency switches on inhibitory control processes after no-go trials. We discuss the theoretical implications of this finding and propose precautions that should be taken into account when studying conflict adaptation using frequency tagging in order to control for the described confounds. Copyright © 2015 Elsevier B.V. All rights reserved.

The role of strategies in motor learning

PubMed Central

Taylor, Jordan A.; Ivry, Richard B.

2015-01-01

There has been renewed interest in the role of strategies in sensorimotor learning. The combination of new behavioral methods and computational methods has begun to unravel the interaction between processes related to strategic control and processes related to motor adaptation. These processes may operate on very different error signals. Strategy learning is sensitive to goal-based performance error. In contrast, adaptation is sensitive to prediction errors between the desired and actual consequences of a planned movement. The former guides what the desired movement should be, whereas the latter guides how to implement the desired movement. Whereas traditional approaches have favored serial models in which an initial strategy-based phase gives way to more automatized forms of control, it now seems that strategic and adaptive processes operate with considerable independence throughout learning, although the relative weight given the two processes will shift with changes in performance. As such, skill acquisition involves the synergistic engagement of strategic and adaptive processes. PMID:22329960

Cognitive control adjustments in healthy older and younger adults: Conflict adaptation, the error-related negativity (ERN), and evidence of generalized decline with age.

PubMed

Larson, Michael J; Clayson, Peter E; Keith, Cierra M; Hunt, Isaac J; Hedges, Dawson W; Nielsen, Brent L; Call, Vaughn R A

2016-03-01

Older adults display alterations in neural reflections of conflict-related processing. We examined response times (RTs), error rates, and event-related potential (ERP; N2 and P3 components) indices of conflict adaptation (i.e., congruency sequence effects) a cognitive control process wherein previous-trial congruency influences current-trial performance, along with post-error slowing, correct-related negativity (CRN), error-related negativity (ERN) and error positivity (Pe) amplitudes in 65 healthy older adults and 94 healthy younger adults. Older adults showed generalized slowing, had decreased post-error slowing, and committed more errors than younger adults. Both older and younger adults showed conflict adaptation effects; magnitude of conflict adaptation did not differ by age. N2 amplitudes were similar between groups; younger, but not older, adults showed conflict adaptation effects for P3 component amplitudes. CRN and Pe, but not ERN, amplitudes differed between groups. Data support generalized declines in cognitive control processes in older adults without specific deficits in conflict adaptation. Copyright © 2016 Elsevier B.V. All rights reserved.

Near-memory data reorganization engine

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

Gokhale, Maya; Lloyd, G. Scott

A memory subsystem package is provided that has processing logic for data reorganization within the memory subsystem package. The processing logic is adapted to reorganize data stored within the memory subsystem package. In some embodiments, the memory subsystem package includes memory units, a memory interconnect, and a data reorganization engine ("DRE"). The data reorganization engine includes a stream interconnect and DRE units including a control processor and a load-store unit. The control processor is adapted to execute instructions to control a data reorganization. The load-store unit is adapted to process data move commands received from the control processor via themore » stream interconnect for loading data from a load memory address of a memory unit and storing data to a store memory address of a memory unit.« less

An Investigation of the Reliability and Self-Regulatory Correlates of Conflict Adaptation.

PubMed

Feldman, Julia L; Freitas, Antonio L

2016-07-01

The study of the conflict-adaptation effect, in which encountering information-processing conflict attenuates the disruptive influence of information-processing conflicts encountered subsequently, is a burgeoning area of research. The present study investigated associations among performance measures on a Stroop-trajectory task (measuring Stroop interference and conflict adaptation), on a Wisconsin Card Sorting Task (WCST; measuring cognitive flexibility), and on self-reported measures of self-regulation (including impulsivity and tenacity). We found significant reliability of the conflict-adaptation effects across a two-week period, for response-time and accuracy. Variability in conflict adaptation was not associated significantly with any indicators of performance on the WCST or with most of the self-reported self-regulation measures. There was substantial covariance between Stroop interference for accuracy and conflict adaptation for accuracy. The lack of evidence of covariance across distinct aspects of cognitive control (conflict adaptation, WCST performance, self-reported self-control) may reflect the operation of relatively independent component processes.

Domain-specific conflict adaptation without feature repetitions.

PubMed

Akçay, Çağlar; Hazeltine, Eliot

2011-06-01

An influential account of how cognitive control deals with conflicting sources of information holds that conflict is monitored by a module that automatically recruits attention to resolve the conflict. This leads to reduced effects of conflict on the subsequent trial, a phenomenon termed conflict adaptation. A prominent question is whether control processes are domain specific--that is, recruited only by the particular type of conflict they resolve. Previous studies that have examined this question used two-choice tasks in which feature repetition effects could be responsible for domain-specific adaptation effects. We report two experiments using four-choice (Experiment 1) and five-choice (Experiment 2) tasks that contain two types of irrelevant sources of potentially conflicting information: stimulus location (Simon conflict) and distractors (flanker conflict). In both experiments, we found within-type conflict adaptation for both types of conflict after eliminating trials on which stimulus features were repeated from one trial to the next. Across-type conflict adaptation, however, was not significant. Thus, conflict adaptation was due to domain-specific recruitment of cognitive control. Our results add converging evidence to the idea that multiple independent control processes are involved in reactive cognitive control, although whether control is always local remains to be determined.

Characteristics of the gait adaptation process due to split-belt treadmill walking under a wide range of right-left speed ratios in humans

PubMed Central

Ogawa, Tetsuya; Yamamoto, Shin-Ichiro; Nakazawa, Kimitaka

2018-01-01

The adaptability of human bipedal locomotion has been studied using split-belt treadmill walking. Most of previous studies utilized experimental protocol under remarkably different split ratios (e.g. 1:2, 1:3, or 1:4). While, there is limited research with regard to adaptive process under the small speed ratios. It is important to know the nature of adaptive process under ratio smaller than 1:2, because systematic evaluation of the gait adaptation under small to moderate split ratios would enable us to examine relative contribution of two forms of adaptation (reactive feedback and predictive feedforward control) on gait adaptation. We therefore examined a gait behavior due to on split-belt treadmill adaptation under five belt speed difference conditions (from 1:1.2 to 1:2). Gait parameters related to reactive control (stance time) showed quick adjustments immediately after imposing the split-belt walking in all five speed ratios. Meanwhile, parameters related to predictive control (step length and anterior force) showed a clear pattern of adaptation and subsequent aftereffects except for the 1:1.2 adaptation. Additionally, the 1:1.2 ratio was distinguished from other ratios by cluster analysis based on the relationship between the size of adaptation and the aftereffect. Our findings indicate that the reactive feedback control was involved in all the speed ratios tested and that the extent of reaction was proportionally dependent on the speed ratio of the split-belt. On the contrary, predictive feedforward control was necessary when the ratio of the split-belt was greater. These results enable us to consider how a given split-belt training condition would affect the relative contribution of the two strategies on gait adaptation, which must be considered when developing rehabilitation interventions for stroke patients. PMID:29694404

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.

Planning assistance for the NASA 30/20 GHz program. Network control architecture study.

NASA Technical Reports Server (NTRS)

Inukai, T.; Bonnelycke, B.; Strickland, S.

1982-01-01

Network Control Architecture for a 30/20 GHz flight experiment system operating in the Time Division Multiple Access (TDMA) was studied. Architecture development, identification of processing functions, and performance requirements for the Master Control Station (MCS), diversity trunking stations, and Customer Premises Service (CPS) stations are covered. Preliminary hardware and software processing requirements as well as budgetary cost estimates for the network control system are given. For the trunking system control, areas covered include on board SS-TDMA switch organization, frame structure, acquisition and synchronization, channel assignment, fade detection and adaptive power control, on board oscillator control, and terrestrial network timing. For the CPS control, they include on board processing and adaptive forward error correction control.

Innate control of adaptive immunity: Beyond the three-signal paradigm

PubMed Central

Jain, Aakanksha; Pasare, Chandrashekhar

2017-01-01

Activation of cells in the adaptive immune system is a highly orchestrated process dictated by multiples cues from the innate immune system. Although the fundamental principles of innate control of adaptive immunity are well established, it is not fully understood how innate cells integrate qualitative pathogenic information in order to generate tailored protective adaptive immune responses. In this review, we discuss complexities involved in the innate control of adaptive immunity that extend beyond T cell receptor engagement, co-stimulation and priming cytokine production but are critical for generation of protective T cell immunity. PMID:28483987

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

Adaptation, Learning, and the Art of War: A Cybernetic Perspective

DTIC Science & Technology

2014-05-14

William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive systems as control loops and the processes of adaptive systems...as a Markov process . Using this model , the study concluded that systems would return to the same relative equilibrium point, expressed in terms of...uncertain and ever-changing environment. Drawing from the works of William Ross Ashby and contemporary cybernetic thought, the study modeled the adaptive

Person Fit Based on Statistical Process Control in an Adaptive Testing Environment. Research Report 98-13.

ERIC Educational Resources Information Center

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

Person-fit research in the context of paper-and-pencil tests is reviewed, and some specific problems regarding person fit in the context of computerized adaptive testing (CAT) are discussed. Some new methods are proposed to investigate person fit in a CAT environment. These statistics are based on Statistical Process Control (SPC) theory. A…

Deficits in context-dependent adaptive coding of reward in schizophrenia

PubMed Central

Kirschner, Matthias; Hager, Oliver M; Bischof, Martin; Hartmann-Riemer, Matthias N; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N; Kaiser, Stefan

2016-01-01

Theoretical principles of information processing and empirical findings suggest that to efficiently represent all possible rewards in the natural environment, reward-sensitive neurons have to adapt their coding range dynamically to the current reward context. Adaptation ensures that the reward system is most sensitive for the most likely rewards, enabling the system to efficiently represent a potentially infinite range of reward information. A deficit in neural adaptation would prevent precise representation of rewards and could have detrimental effects for an organism’s ability to optimally engage with its environment. In schizophrenia, reward processing is known to be impaired and has been linked to different symptom dimensions. However, despite the fundamental significance of coding reward adaptively, no study has elucidated whether adaptive reward processing is impaired in schizophrenia. We therefore studied patients with schizophrenia (n=27) and healthy controls (n=25), using functional magnetic resonance imaging in combination with a variant of the monetary incentive delay task. Compared with healthy controls, patients with schizophrenia showed less efficient neural adaptation to the current reward context, which leads to imprecise neural representation of reward. Importantly, the deficit correlated with total symptom severity. Our results suggest that some of the deficits in reward processing in schizophrenia might be due to inefficient neural adaptation to the current reward context. Furthermore, because adaptive coding is a ubiquitous feature of the brain, we believe that our findings provide an avenue in defining a general impairment in neural information processing underlying this debilitating disorder. PMID:27430009

Adaptive parallel logic networks

NASA Technical Reports Server (NTRS)

Martinez, Tony R.; Vidal, Jacques J.

1988-01-01

Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

A comparison of adaptive and adaptable automation under different levels of environmental stress.

PubMed

Sauer, Juergen; Kao, Chung-Shan; Wastell, David

2012-01-01

The effectiveness of different forms of adaptive and adaptable automation was examined under low- and high-stress conditions, in the form of different levels of noise. Thirty-six participants were assigned to one of the three types of variable automation (adaptive event-based, adaptive performance-based and adaptable serving as a control condition). Participants received 3 h of training on a simulation of a highly automated process control task and were subsequently tested during a 4-h session under noise exposure and quiet conditions. The results for performance suggested no clear benefits of one automation control mode over the other two. However, it emerged that participants under adaptable automation adopted a more active system management strategy and reported higher levels of self-confidence than in the two adaptive control modes. Furthermore, the results showed higher levels of perceived workload, fatigue and anxiety for performance-based adaptive automation control than the other two modes. This study compared two forms of adaptive automation (where the automated system flexibly allocates tasks between human and machine) with adaptable automation (where the human allocates the tasks). The adaptable mode showed marginal advantages. This is of relevance, given that this automation mode may also be easier to design.

Adaptive control of anaerobic digestion processes-a pilot-scale application.

PubMed

Renard, P; Dochain, D; Bastin, G; Naveau, H; Nyns, E J

1988-03-01

A simple adaptive control algorithm, for which theoretical stability and convergence properties had been previously demonstrated, has been successfully implemented on a biomethanation pilot reactor. The methane digester, operated in the CSTR mode was submitted to a shock load, and successfully computer controlled during the subsequent transitory state.

Real time computer controlled weld skate

NASA Technical Reports Server (NTRS)

Wall, W. A., Jr.

1977-01-01

A real time, adaptive control, automatic welding system was developed. This system utilizes the general case geometrical relationships between a weldment and a weld skate to precisely maintain constant weld speed and torch angle along a contoured workplace. The system is compatible with the gas tungsten arc weld process or can be adapted to other weld processes. Heli-arc cutting and machine tool routing operations are possible applications.

Adaptive identification and control of structural dynamics systems using recursive lattice filters

NASA Technical Reports Server (NTRS)

Sundararajan, N.; Montgomery, R. C.; Williams, J. P.

1985-01-01

A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

NASA Technical Reports Server (NTRS)

Kaber, David B.; Prinzel, Lawrence J., III; Wright, Melanie C.; Clamann, Michael P.

2002-01-01

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

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…

Synchronizing theta oscillations with direct-current stimulation strengthens adaptive control in the human brain.

PubMed

Reinhart, Robert M G; Zhu, Julia; Park, Sohee; Woodman, Geoffrey F

2015-07-28

Executive control and flexible adjustment of behavior following errors are essential to adaptive functioning. Loss of adaptive control may be a biomarker of a wide range of neuropsychiatric disorders, particularly in the schizophrenia spectrum. Here, we provide support for the view that oscillatory activity in the frontal cortex underlies adaptive adjustments in cognitive processing following errors. Compared with healthy subjects, patients with schizophrenia exhibited low frequency oscillations with abnormal temporal structure and an absence of synchrony over medial-frontal and lateral-prefrontal cortex following errors. To demonstrate that these abnormal oscillations were the origin of the impaired adaptive control in patients with schizophrenia, we applied noninvasive dc electrical stimulation over the medial-frontal cortex. This noninvasive stimulation descrambled the phase of the low-frequency neural oscillations that synchronize activity across cortical regions. Following stimulation, the behavioral index of adaptive control was improved such that patients were indistinguishable from healthy control subjects. These results provide unique causal evidence for theories of executive control and cortical dysconnectivity in schizophrenia.

Development of flank wear model of cutting tool by using adaptive feedback linear control system on machining AISI D2 steel and AISI 4340 steel

NASA Astrophysics Data System (ADS)

Orra, Kashfull; Choudhury, Sounak K.

2016-12-01

The purpose of this paper is to build an adaptive feedback linear control system to check the variation of cutting force signal to improve the tool life. The paper discusses the use of transfer function approach in improving the mathematical modelling and adaptively controlling the process dynamics of the turning operation. The experimental results shows to be in agreement with the simulation model and error obtained is less than 3%. The state space approach model used in this paper successfully check the adequacy of the control system through controllability and observability test matrix and can be transferred from one state to another by appropriate input control in a finite time. The proposed system can be implemented to other machining process under varying range of cutting conditions to improve the efficiency and observability of the system.

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.

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.

The Use of Statistical Process Control-Charts for Person-Fit Analysis on Computerized Adaptive Testing. LSAC Research Report Series.

ERIC Educational Resources Information Center

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

In this study a cumulative-sum (CUSUM) procedure from the theory of Statistical Process Control was modified and applied in the context of person-fit analysis in a computerized adaptive testing (CAT) environment. Six person-fit statistics were proposed using the CUSUM procedure, and three of them could be used to investigate the CAT in online test…

Theory of psychological adaptive modes.

PubMed

Lehti, Juha

2016-05-01

When an individual is facing a stressor and normal stress-response mechanism cannot guarantee sufficient adaptation, special emotional states, adaptive modes, are activated (for example a depressive reaction). Adaptive modes are involuntary states of mind, they are of comprehensive nature, they interfere with normal functioning, and they cannot be repressed or controlled the same way as many emotions. Their transformational nature differentiates them from other emotional states. The object of the adaptive mode is to optimize the problem-solving abilities according to the situation that has provoked the mode. Cognitions and emotions during the adaptive mode are different than in a normal mental state. These altered cognitions and emotional reactions guide the individual to use the correct coping skills in order to deal with the stressor. Successful adaptation will cause the adaptive mode to fade off since the adaptive mode is no longer necessary, and the process as a whole will lead to raised well-being. However, if the adaptation process is inadequate, then the transformation period is prolonged, and the adaptive mode will turn into a dysfunctional state. Many psychiatric disorders are such maladaptive processes. The maladaptive processes can be turned into functional ones by using adaptive skills that are used in functional adaptive processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Role of Career Adaptabilities for Mid-Career Changers

ERIC Educational Resources Information Center

Brown, Alan; Bimrose, Jenny; Barnes, Sally-Anne; Hughes, Deirdre

2012-01-01

Career adaptability is mediated by personality factors and socio-psychological processes, with learning playing an important role. Using a five-fold career adapt-abilities competency framework (defined here as control, curiosity, commitment, confidence and concern), which was developed from the international quantitative study that is the focus of…

Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

PubMed

Wong, Aaron L; Shelhamer, Mark

2014-05-01

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation. Copyright © 2014 the American Physiological Society.

Contrast Adaptation Implies Two Spatiotemporal Channels but Three Adapting Processes

ERIC Educational Resources Information Center

Langley, Keith; Bex, Peter J.

2007-01-01

The contrast gain control model of adaptation predicts that the effects of contrast adaptation correlate with contrast sensitivity. This article reports that the effects of high contrast spatiotemporal adaptors are maximum when adapting around 19 Hz, which is a factor of two or more greater than the peak in contrast sensitivity. To explain the…

Bayesian nonparametric adaptive control using Gaussian processes.

PubMed

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

2015-03-01

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

Adaptive hybrid optimal quantum control for imprecisely characterized systems.

PubMed

Egger, D J; Wilhelm, F K

2014-06-20

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

Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller.

PubMed

Lin, Chih-Min; Yang, Ming-Shu; Chao, Fei; Hu, Xiao-Min; Zhang, Jun

2016-10-01

This paper aims to propose an efficient network and applies it as an adaptive filter for the signal processing problems. An adaptive filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so that the convergence of the filtering error can be guaranteed. In order to demonstrate the performance of the proposed adaptive T2FCMAC filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an adaptive noise cancellation system. The advantages of the proposed filter over the other adaptive filters are verified through simulations.

Cognitive Control and Conflict Adaptation in Youth with High-Functioning Autism

ERIC Educational Resources Information Center

Larson, Michael J.; South, Mikle; Clayson, Peter E.; Clawson, Ann

2012-01-01

Background: Youth diagnosed with autism spectrum disorders (ASD) often show deficits in cognitive control processes, potentially contributing to characteristic difficulties monitoring and regulating behavior. Modification of performance following conflict can be measured by examining conflict adaptation, the adjustment of cognitive resources based…

Adaptive change in corporate control practices.

PubMed

Alexander, J A

1991-03-01

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

Defense Profiles in Adaptation Process to Sport Competition and Their Relationships with Coping, Stress and Control

PubMed Central

Nicolas, Michel; Martinent, Guillaume; Drapeau, Martin; Chahraoui, Khadija; Vacher, Philippe; de Roten, Yves

2017-01-01

The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control) and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six (N = 296) athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles) of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports. PMID:29312070

Defense Profiles in Adaptation Process to Sport Competition and Their Relationships with Coping, Stress and Control.

PubMed

Nicolas, Michel; Martinent, Guillaume; Drapeau, Martin; Chahraoui, Khadija; Vacher, Philippe; de Roten, Yves

2017-01-01

The purpose of this study was to identify the potentially distinct defense profiles of athletes in order to provide insight into the complex associations that can exist between defenses and other important variables tied to performance in sports (e.g., coping, perceived stress and control) and to further our understanding of the complexity of the adaptation process in sports. Two hundred and ninety-six ( N = 296) athletes participated in a naturalistic study that involved a highly stressful situation: a sports competition. Participants were assessed before and after the competition. Hierarchical cluster analysis and a series of MANOVAs with post hoc comparisons indicated two stable defense profiles (high and low defense profiles) of athletes both before and during sport competition. These profiles differed with regards to coping, stress and control. Athletes with high defense profiles reported higher levels of coping strategies, perceived stress and control than athletes with low defense profiles. This study confirmed that defenses are involved in the psychological adaptation process and that research and intervention should not be based only on coping, but rather must include defense mechanisms in order to improve our understanding of psychological adaptation in competitive sports.

Control assembly for controlling a fuel cell system during shutdown and restart

DOEpatents

Venkataraman, Ramki; Berntsen, George; Carlson, Glenn L.; Farooque, Mohammad; Beachy, Dan; Peterhans, Stefan; Bischoff, Manfred

2010-06-15

A fuel cell system and method in which the fuel cell system receives and an input oxidant gas and an input fuel gas, and in which a fuel processing assembly is provided and is adapted to at least humidify the input fuel gas which is to be supplied to the anode of the fuel cell of the system whose cathode receives the oxidant input gas via an anode oxidizing assembly which is adapted to couple the output of the anode of the fuel cell to the inlet of the cathode of the fuel cell during normal operation, shutdown and restart of the fuel cell system, and in which a control assembly is further provided and is adapted to respond to shutdown of the fuel cell system during which input fuel gas and input oxidant gas cease to be received by the fuel cell system, the control assembly being further adapted to, when the fuel cell system is shut down: control the fuel cell system so as to enable a purging gas to be able to flow through the fuel processing assembly to remove humidified fuel gas from the processing assembly and to enable a purging gas to be able to flow through the anode of the fuel cell.

Research on the adaptive optical control technology based on DSP

NASA Astrophysics Data System (ADS)

Zhang, Xiaolu; Xue, Qiao; Zeng, Fa; Zhao, Junpu; Zheng, Kuixing; Su, Jingqin; Dai, Wanjun

2018-02-01

Adaptive optics is a real-time compensation technique using high speed support system for wavefront errors caused by atmospheric turbulence. However, the randomness and instantaneity of atmospheric changing introduce great difficulties to the design of adaptive optical systems. A large number of complex real-time operations lead to large delay, which is an insurmountable problem. To solve this problem, hardware operation and parallel processing strategy are proposed, and a high-speed adaptive optical control system based on DSP is developed. The hardware counter is used to check the system. The results show that the system can complete a closed loop control in 7.1ms, and improve the controlling bandwidth of the adaptive optical system. Using this system, the wavefront measurement and closed loop experiment are carried out, and obtain the good results.

The influence of approach-avoidance motivational orientation on conflict adaptation.

PubMed

Hengstler, Maikel; Holland, Rob W; van Steenbergen, Henk; van Knippenberg, Ad

2014-06-01

To deal effectively with a continuously changing environment, our cognitive system adaptively regulates resource allocation. Earlier findings showed that an avoidance orientation (induced by arm extension), relative to an approach orientation (induced by arm flexion), enhanced sustained cognitive control. In avoidance conditions, performance on a cognitive control task was enhanced, as indicated by a reduced congruency effect, relative to approach conditions. Extending these findings, in the present behavioral studies we investigated dynamic adaptations in cognitive control-that is, conflict adaptation. We proposed that an avoidance state recruits more resources in response to conflicting signals, and thereby increases conflict adaptation. Conversely, in an approach state, conflict processing diminishes, which consequently weakens conflict adaptation. As predicted, approach versus avoidance arm movements affected both behavioral congruency effects and conflict adaptation: As compared to approach, avoidance movements elicited reduced congruency effects and increased conflict adaptation. These results are discussed in line with a possible underlying neuropsychological model.

Telerobotic control of a mobile coordinated robotic server, executive summary

NASA Technical Reports Server (NTRS)

Lee, Gordon

1993-01-01

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University.

Developments in Signature Process Control

NASA Astrophysics Data System (ADS)

Keller, L. B.; Dominski, Marty

1993-01-01

Developments in the adaptive process control technique known as Signature Process Control for Advanced Composites (SPCC) are described. This computer control method for autoclave processing of composites was used to develop an optimum cure cycle for AFR 700B polyamide and for an experimental poly-isoimide. An improved process cycle was developed for Avimid N polyamide. The potential for extending the SPCC technique to pre-preg quality control, press modeling, pultrusion and RTM is briefly discussed.

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.

Aircraft adaptive learning control

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

NASA Technical Reports Server (NTRS)

Pavlock, Kate M.

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration, experiment functionality, overall risk mitigation, flight test approach and results, and lessons learned of adaptive controls research of the Full-Scale Advanced Systems Testbed.

Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.

PubMed

Aprasoff, Jonathan; Donchin, Opher

2012-04-01

Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.

Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.

Use of beam deflection to control an electron beam wire deposition process

NASA Technical Reports Server (NTRS)

Taminger, Karen M. (Inventor); Hofmeister, William H. (Inventor); Hafley, Robert A. (Inventor)

2013-01-01

A method for controlling an electron beam process wherein a wire is melted and deposited on a substrate as a molten pool comprises generating the electron beam with a complex raster pattern, and directing the beam onto an outer surface of the wire to thereby control a location of the wire with respect to the molten pool. Directing the beam selectively heats the outer surface of the wire and maintains the position of the wire with respect to the molten pool. An apparatus for controlling an electron beam process includes a beam gun adapted for generating the electron beam, and a controller adapted for providing the electron beam with a complex raster pattern and for directing the electron beam onto an outer surface of the wire to control a location of the wire with respect to the molten pool.

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Verification and Validation of Neural Networks for Aerospace Systems

NASA Technical Reports Server (NTRS)

Mackall, Dale; Nelson, Stacy; Schumman, Johann; Clancy, Daniel (Technical Monitor)

2002-01-01

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: 1) Overview of Adaptive Systems; and 2) V&V Processes/Methods.

Verification and Validation of Neural Networks for Aerospace Systems

NASA Technical Reports Server (NTRS)

Mackall, Dale; Nelson, Stacy; Schumann, Johann

2002-01-01

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: Overview of Adaptive Systems and V&V Processes/Methods.

Real-time control system for adaptive resonator

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

Flath, L; An, J; Brase, J

2000-07-24

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

Adaptive array antenna for satellite cellular and direct broadcast communications

NASA Technical Reports Server (NTRS)

Horton, Charles R.; Abend, Kenneth

1993-01-01

Adaptive phased-array antennas provide cost-effective implementation of large, light weight apertures with high directivity and precise beamshape control. Adaptive self-calibration allows for relaxation of all mechanical tolerances across the aperture and electrical component tolerances, providing high performance with a low-cost, lightweight array, even in the presence of large physical distortions. Beam-shape is programmable and adaptable to changes in technical and operational requirements. Adaptive digital beam-forming eliminates uplink contention by allowing a single electronically steerable antenna to service a large number of receivers with beams which adaptively focus on one source while eliminating interference from others. A large, adaptively calibrated and fully programmable aperture can also provide precise beam shape control for power-efficient direct broadcast from space. Advanced adaptive digital beamforming technologies are described for: (1) electronic compensation of aperture distortion, (2) multiple receiver adaptive space-time processing, and (3) downlink beam-shape control. Cost considerations for space-based array applications are also discussed.

Adaptive-randomised self-calibration of electro-mechanical shutters for space imaging

NASA Astrophysics Data System (ADS)

De Cecco, Mariolino; Debei, Stefano; Zaccariotto, Mirco; Pertile, Marco

2006-11-01

This work describes the self-calibration of a high-precision open-loop mechanism. The self-calibration method is applied to a mechanical shutter for space applications, which was launched onboard the ESA-ROSETTA mission (launch: 2 March 2004). It is based on an adaptive 'model reference' and a 'randomised' search method which may be generalised to applications in which high performance and functionality are strongly interconnected. The method makes use of an adaptive 'model-reference' control approach [K.J. Astrom, B. Wittenmark, On self-tuning regulators Automatica 9 (1973) 185-199 [16]; K.J. Astrom, Theory and application of adaptive control, in: Proceedings of the Eighth IFAC World Conference, Kyoto, Japan, 1981 [17]; D.E. Seborg, S.L. Shah, T.F. Edgar, Adaptive control strategies for process control, AIChE Journal 6(32) (1986) 881-895 [18

Adaptation to sensory-motor reflex perturbations is blind to the source of errors.

PubMed

Hudson, Todd E; Landy, Michael S

2012-01-06

In the study of visual-motor control, perhaps the most familiar findings involve adaptation to externally imposed movement errors. Theories of visual-motor adaptation based on optimal information processing suppose that the nervous system identifies the sources of errors to effect the most efficient adaptive response. We report two experiments using a novel perturbation based on stimulating a visually induced reflex in the reaching arm. Unlike adaptation to an external force, our method induces a perturbing reflex within the motor system itself, i.e., perturbing forces are self-generated. This novel method allows a test of the theory that error source information is used to generate an optimal adaptive response. If the self-generated source of the visually induced reflex perturbation is identified, the optimal response will be via reflex gain control. If the source is not identified, a compensatory force should be generated to counteract the reflex. Gain control is the optimal response to reflex perturbation, both because energy cost and movement errors are minimized. Energy is conserved because neither reflex-induced nor compensatory forces are generated. Precision is maximized because endpoint variance is proportional to force production. We find evidence against source-identified adaptation in both experiments, suggesting that sensory-motor information processing is not always optimal.

Techniques for grid manipulation and adaptation. [computational fluid dynamics

NASA Technical Reports Server (NTRS)

Choo, Yung K.; Eisemann, Peter R.; Lee, Ki D.

1992-01-01

Two approaches have been taken to provide systematic grid manipulation for improved grid quality. One is the control point form (CPF) of algebraic grid generation. It provides explicit control of the physical grid shape and grid spacing through the movement of the control points. It works well in the interactive computer graphics environment and hence can be a good candidate for integration with other emerging technologies. The other approach is grid adaptation using a numerical mapping between the physical space and a parametric space. Grid adaptation is achieved by modifying the mapping functions through the effects of grid control sources. The adaptation process can be repeated in a cyclic manner if satisfactory results are not achieved after a single application.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Evolving Systems: An Outcome of Fondest Hopes and Wildest Dreams

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.

2012-01-01

New theory is presented for evolving systems, which are autonomously controlled subsystems that self-assemble into a new evolved system with a higher purpose. Evolving systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control that operates through one specific component to maintain stability during the evolution. In addition, this control must often overcome persistent disturbances that occur while the evolution is in progress. Theoretical results will be presented for Adaptive Key Component control for persistent disturbance rejection. An illustrative example will demonstrate the Adaptive Key Component controller on a system composed of rigid body and flexible body modes.

Genetic algorithms in adaptive fuzzy control

NASA Technical Reports Server (NTRS)

Karr, C. Lucas; Harper, Tony R.

1992-01-01

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

No evidence for common processes of cognitive control and self-control.

PubMed

Scherbaum, Stefan; Frisch, Simon; Holfert, Anna-Maria; O'Hora, Denis; Dshemuchadse, Maja

2018-01-01

Cognitive control and self-control are often used as interchangeable terms. Both terms refer to the ability to pursue long-term goals, but the types of controlled behavior that are typically associated with these terms differ, at least superficially. Cognitive control is observed in the control of attention and the overcoming of habitual responses, while self-control is observed in resistance to short-term impulses and temptations. Evidence from clinical studies and neuroimaging studies suggests that below these superficial differences, common control process (e.g., inhibition) might guide both types of controlled behavior. Here, we study this hypothesis in a behavioral experiment, which interlaced trials of a Simon task with trials of an intertemporal decision task. If cognitive control and self-control depend on a common control process, we expected conflict adaptation from Simon task trials to lead to increased self-control in the intertemporal decision trials. However, despite successful manipulations of conflict and conflict adaptation, we found no evidence for this hypothesis. We investigate a number of alternative explanations of this result and conclude that the differences between cognitive control and self-control are not superficial, but rather reflect differences at the process level. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive independent joint control of manipulators - Theory and experiment

NASA Technical Reports Server (NTRS)

Seraji, H.

1988-01-01

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

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

Which Measures of Online Control Are Least Sensitive to Offline Processes?

PubMed

de Grosbois, John; Tremblay, Luc

2018-02-28

A major challenge to the measurement of online control is the contamination by offline, planning-based processes. The current study examined the sensitivity of four measures of online control to offline changes in reaching performance induced by prism adaptation and terminal feedback. These measures included the squared Z scores (Z 2 ) of correlations of limb position at 75% movement time versus movement end, variable error, time after peak velocity, and a frequency-domain analysis (pPower). The results indicated that variable error and time after peak velocity were sensitive to the prism adaptation. Furthermore, only the Z 2 values were biased by the terminal feedback. Ultimately, the current study has demonstrated the sensitivity of limb kinematic measures to offline control processes and that pPower analyses may yield the most suitable measure of online control.

Prediction and control of chaotic processes using nonlinear adaptive networks

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

Jones, R.D.; Barnes, C.W.; Flake, G.W.

1990-01-01

We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

Sensory Processing in Preterm Preschoolers and Its Association with Executive Function

PubMed Central

Adams, Jenna N.; Feldman, Heidi M.; Huffman, Lynne C.; Loe, Irene M.

2015-01-01

Background Symptoms of abnormal sensory processing have been related to preterm birth, but have not yet been studied specifically in preterm preschoolers. The degree of association between sensory processing and other domains is important for understanding the role of sensory processing symptoms in the development of preterm children. Aims To test two related hypotheses: (1) preterm preschoolers have more sensory processing symptoms than full term preschoolers and (2) sensory processing is associated with both executive function and adaptive function in preterm preschoolers. Study Design Cross-sectional study Subjects Preterm children (≤34 weeks of gestation; n = 54) and full term controls (≥37 weeks of gestation; n = 73) ages 3-5 years. Outcome Measures Sensory processing was assessed with the Short Sensory Profile. Executive function was assessed with (1) parent ratings on the Behavior Rating Inventory of Executive Function- Preschool version and (2) a performance-based battery of tasks. Adaptive function was assessed with the Vineland Adaptive Behavior Scales-II. Results Preterm preschoolers showed significantly more sensory symptoms than full term controls. A higher percentage of preterm than full term preschoolers had elevated numbers of sensory symptoms (37% vs. 12%). Sensory symptoms in preterm preschoolers were associated with scores on executive function measures, but were not significantly associated with adaptive function. Conclusions Preterm preschoolers exhibited more sensory symptoms than full term controls. Preterm preschoolers with elevated numbers of sensory symptoms also showed executive function impairment. Future research should further examine whether sensory processing and executive function should be considered independent or overlapping constructs. PMID:25706317

Adaptation of a U.S. evidence-based Positive Prevention intervention for youth living with HIV/AIDS in Kinshasa, Democratic Republic of the Congo

PubMed Central

Parker, L.; Maman, S.; Pettifor, A.; Chalachala, J.L.; Edmonds, A.; Golin, C.E.; Moracco, K.; Behets, F.

2013-01-01

Effective HIV prevention programs for people living with HIV/AIDS (PLWH) are important to reduce new infections and to ensure PLWH remain healthy. This paper describes the systematic adaptation of a U.S.-developed Evidence Based Intervention (EBI) using the Centers for Disease Control and Prevention (CDC) Map of Adaption Process for use at a Pediatric Hospital in Kinshasa, Democratic Republic of the Congo (DRC). The adapted intervention, Supporting Youth and Motivating Positive Action or SYMPA, a six-session risk reduction intervention targeted for youth living with HIV/AIDS (YLWH) in Kinshasa was adapted from the Healthy Living Project and guided by the Social Action Theory. This paper describes the process of implementing the first four steps of the ADAPT framework (Assess, Select, Prepare, and Pilot). Our study has shown that an EBI developed and implemented in the U.S. can be adapted successfully for a different target population in a low-resource context through an iterative process following the CDC ADAPT framework. This process included reviewing existing literature, adapting and adding components, and focusing on increasing staff capacity. This paper provides a rare, detailed description of the adaptation process and may aid organizations seeking to adapt and implement HIV prevention EBIs in sub-Saharan Africa and beyond. PMID:23063699

Adaptive management for ecosystem services (j/a) | Science ...

EPA Pesticide Factsheets

Management of natural resources for the production of ecosystem services, which are vital for human well-being, is necessary even when there is uncertainty regarding system response to management action. This uncertainty is the result of incomplete controllability, complex internal feedbacks, and non-linearity that often interferes with desired management outcomes, and insufficient understanding of nature and people. Adaptive management was developed to reduce such uncertainty. We present a framework for the application of adaptive management for ecosystem services that explicitly accounts for cross-scale tradeoffs in the production of ecosystem services. Our framework focuses on identifying key spatiotemporal scales (plot, patch, ecosystem, landscape, and region) that encompass dominant structures and processes in the system, and includes within- and cross-scale dynamics, ecosystem service tradeoffs, and management controllability within and across scales. Resilience theory recognizes that a limited set of ecological processes in a given system regulate ecosystem services, yet our understanding of these processes is poorly understood. If management actions erode or remove these processes, the system may shift into an alternative state unlikely to support the production of desired services. Adaptive management provides a process to assess the underlying within and cross-scale tradeoffs associated with production of ecosystem services while proceeding with manage

Adaptive and predictive control of a simulated robot arm.

PubMed

Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

2013-06-01

In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs).

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

NASA Astrophysics Data System (ADS)

Tin, Chung; Poon, Chi-Sang

2005-09-01

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

Adaptive/learning control of large space structures - System identification techniques. [for multi-configuration flexible spacecraft

NASA Technical Reports Server (NTRS)

Thau, F. E.; Montgomery, R. C.

1980-01-01

Techniques developed for the control of aircraft under changing operating conditions are used to develop a learning control system structure for a multi-configuration, flexible space vehicle. A configuration identification subsystem that is to be used with a learning algorithm and a memory and control process subsystem is developed. Adaptive gain adjustments can be achieved by this learning approach without prestoring of large blocks of parameter data and without dither signal inputs which will be suppressed during operations for which they are not compatible. The Space Shuttle Solar Electric Propulsion (SEP) experiment is used as a sample problem for the testing of adaptive/learning control system algorithms.

Robustness of reduced-order multivariable state-space self-tuning controller

NASA Technical Reports Server (NTRS)

Yuan, Zhuzhi; Chen, Zengqiang

1994-01-01

In this paper, we present a quantitative analysis of the robustness of a reduced-order pole-assignment state-space self-tuning controller for a multivariable adaptive control system whose order of the real process is higher than that of the model used in the controller design. The result of stability analysis shows that, under a specific bounded modelling error, the adaptively controlled closed-loop real system via the reduced-order state-space self-tuner is BIBO stable in the presence of unmodelled dynamics.

Cultural adaptation of an evidence-based nursing intervention to improve medication adherence among people living with HIV/AIDS (PLWHA) in China.

PubMed

Williams, Ann B; Wang, Honghong; Burgess, Jane; Li, Xianhong; Danvers, Karina

2013-04-01

Adapting nursing interventions to suit the needs and culture of a new population (cultural adaptation) is an important early step in the process of implementation and dissemination. While the need for cultural adaptation is widely accepted, research-based strategies for doing so are not well articulated. Non-adherence to medications for chronic disease is a global problem and cultural adaptation of existing evidence-based interventions could be useful. This paper aims to describe the cultural adaptation of an evidence-based nursing intervention to improve medication adherence among people living with HIV/AIDS and to offer recommendations for adaptation of interventions across cultures and borders. SITE: The intervention, which demonstrated efficacy in a randomized controlled trial in North America, was adapted for the cultural and social context of Hunan Province, in south central China. The adaptation process was undertaken by intervention stakeholders including the original intervention study team, the proposed adaptation team, and members of a Community Advisory Board, including people living with HIV/AIDS, family members, and health care workers at the target clinical sites. The adaptation process was driven by quantitative and qualitative data describing the new population and context and was guided by principles for cultural adaptation drawn from prevention science research. The primary adaptation to the intervention was the inclusion of family members in intervention activities, in response to the cultural and social importance of the family in rural China. In a pilot test of the adapted intervention, self-reported medication adherence improved significantly in the group receiving the intervention compared to the control group (p=0.01). Recommendations for cultural adaptation of nursing interventions include (1) involve stakeholders from the beginning; (2) assess the population, need, and context; (3) evaluate the intervention to be adapted with attention to details of the original studies that demonstrated efficacy; (4) compare important elements of the original intervention with those of the proposed new population and context to identify primary points for adaptation; (5) explicitly identify sources of tension between intervention fidelity and cultural adaptive needs; (6) document the process of adaptation, pilot the adapted intervention, and evaluate its effectiveness before moving to dissemination and implementation on a large scale. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2006-09-01

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

Methods of Adapting Digital Content for the Learning Process via Mobile Devices

ERIC Educational Resources Information Center

Lopez, J. L. Gimenez; Royo, T. Magal; Laborda, Jesus Garcia; Calvo, F. Garde

2009-01-01

This article analyses different methods of adapting digital content for its delivery via mobile devices taking into account two aspects which are a fundamental part of the learning process; on the one hand, functionality of the contents, and on the other, the actual controlled navigation requirements that the learner needs in order to acquire high…

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…

Editorial overview: Pests and resistance: Shedding the albatross of resistance starts by embracing the ecological complexities of its evolution

USDA-ARS?s Scientific Manuscript database

Adaptation of a species to a pest control measure, such as an insecticide, involves essentially the same evolutionary processes that result in adaptation to any environmental stressor. The living insects targeted by a control tactic are the latest product of countless generations of natural selectio...

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum.

PubMed

Wilson, Emma D; Assaf, Tareq; Pearson, Martin J; Rossiter, Jonathan M; Dean, Paul; Anderson, Sean R; Porrill, John

2015-01-01

The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

Adapting Hypertension Self-Management Interventions to Enhance their Sustained Effectiveness among Urban African Americans

PubMed Central

Ameling, Jessica M.; Ephraim, Patti L.; Bone, Lee R.; Levine, David M.; Roter, Debra L.; Wolff, Jennifer L.; Hill-Briggs, Felicia; Fitzpatrick, Stephanie L.; Noronha, Gary J.; Fagan, Peter J.; Lewis-Boyer, LaPricia; Hickman, Debra; Simmons, Michelle; Purnell, Leon; Fisher, Annette; Cooper, Lisa A.; Aboumatar, Hanan J.; Albert, Michael C.; Flynn, Sarah J.; Boulware, L. Ebony

2014-01-01

African Americans suffer disproportionately poor hypertension control despite the availability of efficacious interventions. Using principles of community-based participatory research and implementation science, we adapted established hypertension self-management interventions to enhance interventions’ cultural relevance and potential for sustained effectiveness among urban African Americans. We obtained input from patients and their family members, their health care providers, and community members. The process required substantial time and resources, and the adapted interventions will be tested in a randomized controlled trial. PMID:24569158

Adapting hypertension self-management interventions to enhance their sustained effectiveness among urban African Americans.

PubMed

Ameling, Jessica M; Ephraim, Patti L; Bone, Lee R; Levine, David M; Roter, Debra L; Wolff, Jennifer L; Hill-Briggs, Felicia; Fitzpatrick, Stephanie L; Noronha, Gary J; Fagan, Peter J; Lewis-Boyer, LaPricia; Hickman, Debra; Simmons, Michelle; Purnell, Leon; Fisher, Annette; Cooper, Lisa A; Aboumatar, Hanan J; Albert, Michael C; Flynn, Sarah J; Boulware, L Ebony

2014-01-01

African Americans suffer disproportionately poor hypertension control despite the availability of efficacious interventions. Using principles of community-based participatory research and implementation science, we adapted established hypertension self-management interventions to enhance interventions' cultural relevance and potential for sustained effectiveness among urban African Americans. We obtained input from patients and their family members, their health care providers, and community members. The process required substantial time and resources, and the adapted interventions will be tested in a randomized controlled trial.

An Adaptive Method of Lines with Error Control for Parabolic Equations of the Reaction-Diffusion Type.

DTIC Science & Technology

1984-06-01

space discretization error . 1. I 3 1. INTRODUCTION Reaction- diffusion processes occur in many branches of biology and physical chemistry. Examples...to model reaction- diffusion phenomena. The primary goal of this adaptive method is to keep a particular norm of the space discretization error less...AD-A142 253 AN ADAPTIVE MET6 OFD LNES WITH ERROR CONTROL FOR 1 INST FOR PHYSICAL SCIENCE AND TECH. I BABUSKAAAO C7 EA OH S UMR AN UNVC EEP R

Uncertainty and Cognitive Control

PubMed Central

Mushtaq, Faisal; Bland, Amy R.; Schaefer, Alexandre

2011-01-01

A growing trend of neuroimaging, behavioral, and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1) There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2) There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3) The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the “need for control”; (4) Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders. PMID:22007181

Fuzzy control of burnout of multilayer ceramic actuators

NASA Astrophysics Data System (ADS)

Ling, Alice V.; Voss, David; Christodoulou, Leo

1996-08-01

To improve the yield and repeatability of the burnout process of multilayer ceramic actuators (MCAs), an intelligent processing of materials (IPM-based) control system has been developed for the manufacture of MCAs. IPM involves the active (ultimately adaptive) control of a material process using empirical or analytical models and in situ sensing of critical process states (part features and process parameters) to modify the processing conditions in real time to achieve predefined product goals. Thus, the three enabling technologies for the IPM burnout control system are process modeling, in situ sensing and intelligent control. This paper presents the design of an IPM-based control strategy for the burnout process of MCAs.

Feedback and feedforward adaptation to visuomotor delay during reaching and slicing movements.

PubMed

Botzer, Lior; Karniel, Amir

2013-07-01

It has been suggested that the brain and in particular the cerebellum and motor cortex adapt to represent the environment during reaching movements under various visuomotor perturbations. It is well known that significant delay is present in neural conductance and processing; however, the possible representation of delay and adaptation to delayed visual feedback has been largely overlooked. Here we investigated the control of reaching movements in human subjects during an imposed visuomotor delay in a virtual reality environment. In the first experiment, when visual feedback was unexpectedly delayed, the hand movement overshot the end-point target, indicating a vision-based feedback control. Over the ensuing trials, movements gradually adapted and became accurate. When the delay was removed unexpectedly, movements systematically undershot the target, demonstrating that adaptation occurred within the vision-based feedback control mechanism. In a second experiment designed to broaden our understanding of the underlying mechanisms, we revealed similar after-effects for rhythmic reversal (out-and-back) movements. We present a computational model accounting for these results based on two adapted forward models, each tuned for a specific modality delay (proprioception or vision), and a third feedforward controller. The computational model, along with the experimental results, refutes delay representation in a pure forward vision-based predictor and suggests that adaptation occurred in the forward vision-based predictor, and concurrently in the state-based feedforward controller. Understanding how the brain compensates for conductance and processing delays is essential for understanding certain impairments concerning these neural delays as well as for the development of brain-machine interfaces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Is conflict adaptation due to active regulation or passive carry-over? Evidence from eye movements.

PubMed

Hubbard, Jason; Kuhns, David; Schäfer, Theo A J; Mayr, Ulrich

2017-03-01

Conflict-adaptation effects (i.e., reduced response-time costs on high-conflict trials following high-conflict trials) supposedly represent our cognitive system's ability to regulate itself according to current processing demands. However, currently it is not clear whether these effects reflect conflict-triggered, active regulation, or passive carry-over of previous-trial control settings. We used eye movements to examine whether the degree of experienced conflict modulates conflict-adaptation effects, as the conflict-triggered regulation view predicts. Across 2 experiments in which participants had to identify a target stimulus based on an endogenous cue while-on conflict trials-having to resist a sudden-onset distractor, we found a clear indication of conflict adaptation. This adaptation effect disappeared however, when participants inadvertently fixated the sudden-onset distractor on the previous trial-that is, when they experienced a high degree of conflict. This pattern of results suggests that conflict adaptation can be explained parsimoniously in terms of a broader memory process that retains recently adopted control settings across trials. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Is Conflict Adaptation due to Active Regulation or Passive Carry-Over? Evidence from Eye Movements

PubMed Central

Hubbard, Jason; Kuhns, David; Schäfer, Theo A.J.; Mayr, Ulrich

2017-01-01

Conflict-adaptation effects (i.e., reduced response-time costs on high-conflict trials following high-conflict trials) supposedly represent our cognitive system’s ability to regulate itself according to current processing demands. However, currently it is not clear whether these effects reflect conflict-triggered, active regulation, or passive carry-over of previous-trial control settings. We used eye movements to examine whether the degree of experienced conflict modulates conflict-adaptation effects, as the conflict-triggered regulation view predicts. Across two experiments in which participants had to identify a target stimulus based on an endogenous cue while––on conflict trials––having to resist a sudden-onset distractor, we found a clear indication of conflict adaptation. This adaptation effect disappeared however, when participants inadvertently fixated the sudden-onset distractor on the previous trial––that is, when they experienced a high degree of conflict. This pattern of results suggests that conflict adaptation can be explained parsimoniously in terms of a broader memory process that retains recently adopted control settings across trials. PMID:27656869

Control allocation-based adaptive control for greenhouse climate

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

1997-01-01

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

Adaptation of social and non-social cues to direction in adults with autism spectrum disorder and neurotypical adults with autistic traits.

PubMed

Lawson, Rebecca P; Aylward, Jessica; Roiser, Jonathan P; Rees, Geraint

2018-01-01

Perceptual constancy strongly relies on adaptive gain control mechanisms, which shift perception as a function of recent sensory history. Here we examined the extent to which individual differences in magnitude of adaptation aftereffects for social and non-social directional cues are related to autistic traits and sensory sensitivity in healthy participants (Experiment 1); and also whether adaptation for social and non-social directional cues is differentially impacted in adults with Autism Spectrum Disorder (ASD) relative to neurotypical (NT) controls (Experiment 2). In Experiment 1, individuals with lower susceptibility to adaptation aftereffects, i.e. more 'veridical' perception, showed higher levels of autistic traits across social and non-social stimuli. Furthermore, adaptation aftereffects were predictive of sensory sensitivity. In Experiment 2, only adaptation to eye-gaze was diminished in adults with ASD, and this was related to difficulties categorizing eye-gaze direction at baseline. Autism Diagnostic Observation Schedule (ADOS) scores negatively predicted lower adaptation for social (head and eye-gaze direction) but not non-social (chair) stimuli. These results suggest that the relationship between adaptation and the broad socio-cognitive processing style captured by 'autistic traits' may be relatively domain-general, but in adults with ASD diminished adaptation is only apparent where processing is most severely impacted, such as the perception of social attention cues. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Safety assurance of non-deterministic flight controllers in aircraft applications

NASA Astrophysics Data System (ADS)

Noriega, Alfonso

Loss of control is a serious problem in aviation that primarily affects General Aviation. Technological advancements can help mitigate the problem, but the FAA certification process makes certain solutions economically unfeasible. This investigation presents the design of a generic adaptive autopilot that could potentially lead to a single certification for use in several makes and models of aircraft. The autopilot consists of a conventional controller connected in series with a robust direct adaptive model reference controller. In this architecture, the conventional controller is tuned once to provide outer-loop guidance and navigation to a reference model. The adaptive controller makes unknown aircraft behave like the reference model, allowing the conventional controller to successfully provide navigation without the need for retuning. A strong theoretical foundation is presented as an argument for the safety and stability of the controller. The stability proof of direct adaptive controllers require that the plant being controlled has no unstable transmission zeros and has a nonzero high frequency gain. Because most conventional aircraft do not readily meet these requirements, a process known as sensor blending was used. Sensor blending consists of using a linear combination of the plant's outputs that has no unstable transmission zeros and has a nonzero high frequency gain to drive the adaptive controller. Although this method does not present a problem for regulators, it can lead to a steady state error in tracking applications. The sensor blending theory was expanded to take advantage of the system's dynamics to allow for zero steady state error tracking. This method does not need knowledge of the specific system's dynamics, but instead uses the structure of the A and B matrices to perform the blending for the general case. The generic adaptive autopilot was tested in two high-fidelity nonlinear simulators of two typical General Aviation aircraft. The results show that the autopilot was able to adapt appropriately to the different aircraft and was able to perform three-dimensional navigation and an ILS approach, without any modification to the controller. The autopilot was tested in moderate atmospheric turbulence, using consumer-grade sensors and actuators currently available in General Aviation aircraft. The generic adaptive autopilot was shown to be robust to atmospheric turbulence and sensor and actuator random noise. In both aircraft simulators, the autopilot adapted successfully to changes in airspeed, altitude, and configuration. This investigation proves the feasibility of a generic autopilot using direct adaptive controller. The autopilot does not need a priori information of the specific aircraft's dynamics to maintain its safety and stability arguments. Real-time parameter estimation of the aircraft dynamics are not needed. Recommendations for future work are provided.

Nonlinear versus Ordinary Adaptive Control of Continuous Stirred-Tank Reactor

PubMed Central

Dostal, Petr

2015-01-01

Unfortunately, the major group of the systems in industry has nonlinear behavior and control of such processes with conventional control approaches with fixed parameters causes problems and suboptimal or unstable control results. An adaptive control is one way to how we can cope with nonlinearity of the system. This contribution compares classic adaptive control and its modification with Wiener system. This configuration divides nonlinear controller into the dynamic linear part and the static nonlinear part. The dynamic linear part is constructed with the use of polynomial synthesis together with the pole-placement method and the spectral factorization. The static nonlinear part uses static analysis of the controlled plant for introducing the mathematical nonlinear description of the relation between the controlled output and the change of the control input. Proposed controller is tested by the simulations on the mathematical model of the continuous stirred-tank reactor with cooling in the jacket as a typical nonlinear system. PMID:26346878

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.

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

NASA Technical Reports Server (NTRS)

Burken, John J.; Larson, Richard R.

2009-01-01

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

The adaptive nature of eye movements in linguistic tasks: how payoff and architecture shape speed-accuracy trade-offs.

PubMed

Lewis, Richard L; Shvartsman, Michael; Singh, Satinder

2013-07-01

We explore the idea that eye-movement strategies in reading are precisely adapted to the joint constraints of task structure, task payoff, and processing architecture. We present a model of saccadic control that separates a parametric control policy space from a parametric machine architecture, the latter based on a small set of assumptions derived from research on eye movements in reading (Engbert, Nuthmann, Richter, & Kliegl, 2005; Reichle, Warren, & McConnell, 2009). The eye-control model is embedded in a decision architecture (a machine and policy space) that is capable of performing a simple linguistic task integrating information across saccades. Model predictions are derived by jointly optimizing the control of eye movements and task decisions under payoffs that quantitatively express different desired speed-accuracy trade-offs. The model yields distinct eye-movement predictions for the same task under different payoffs, including single-fixation durations, frequency effects, accuracy effects, and list position effects, and their modulation by task payoff. The predictions are compared to-and found to accord with-eye-movement data obtained from human participants performing the same task under the same payoffs, but they are found not to accord as well when the assumptions concerning payoff optimization and processing architecture are varied. These results extend work on rational analysis of oculomotor control and adaptation of reading strategy (Bicknell & Levy, ; McConkie, Rayner, & Wilson, 1973; Norris, 2009; Wotschack, 2009) by providing evidence for adaptation at low levels of saccadic control that is shaped by quantitatively varying task demands and the dynamics of processing architecture. Copyright © 2013 Cognitive Science Society, Inc.

The gravitational field and brain function.

PubMed

Mei, L; Zhou, C D; Lan, J Q; Wang, Z G; Wu, W C; Xue, X M

1983-01-01

The frontal cortex is recognized as the highest adaptive control center of the human brain. The principle of the "frontalization" of human brain function offers new possibilities for brain research in space. There is evolutionary and experimental evidence indicating the validity of the principle, including it's role in nervous response to gravitational stimulation. The gravitational field is considered here as one of the more constant and comprehensive factors acting on brain evolution, which has undergone some successive crucial steps: "encephalization", "corticalization", "lateralization" and "frontalization". The dominating effects of electrical responses from the frontal cortex have been discovered 1) in experiments under gravitational stimulus; and 2) in processes potentially relating to gravitational adaptation, such as memory and learning, sensory information processing, motor programing, and brain state control. A brain research experiment during space flight is suggested to test the role of the frontal cortex in space adaptation and it's potentiality in brain control.

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Conflict monitoring and adaptation as reflected by N2 amplitude in obsessive-compulsive disorder.

PubMed

Riesel, A; Klawohn, J; Kathmann, N; Endrass, T

2017-06-01

Feelings of doubt and perseverative behaviours are key symptoms of obsessive-compulsive disorder (OCD) and have been linked to hyperactive error and conflict signals in the brain. While enhanced neural correlates of error monitoring have been robustly shown, far less is known about conflict processing and adaptation in OCD. We examined event-related potentials during conflict processing in 70 patients with OCD and 70 matched healthy comparison participants, focusing on the stimulus-locked N2 elicited in a flanker task. Conflict adaptation was evaluated by analysing sequential adjustments in N2 and behaviour, i.e. current conflict effects as a function of preceding conflict. Patients with OCD showed enhanced N2 amplitudes compared with healthy controls. Further, patients showed stronger conflict adaptation effects on reaction times and N2 amplitude. Thus, the effect of previous compatibility was larger in patients than in healthy participants as indicated by greater N2 adjustments in change trials (i.e. iC, cI). As a result of stronger conflict adaptation in patients, N2 amplitudes were comparable between groups in incompatible trials following incompatible trials. Larger N2 amplitudes and greater conflict adaptation in OCD point to enhanced conflict monitoring leading to increased recruitment of cognitive control in patients. This was most pronounced in change trials and was associated with stronger conflict adjustment in N2 and behaviour. Thus, hyperactive conflict monitoring in OCD may be beneficial in situations that require a high amount of control to resolve conflict, but may also reflect an effortful process that is linked to distress and symptoms of OCD.

Feedback control methods for drug dosage optimisation. Concepts, classification and clinical application.

PubMed

Vozeh, S; Steimer, J L

1985-01-01

The concept of feedback control methods for drug dosage optimisation is described from the viewpoint of control theory. The control system consists of 5 parts: (a) patient (the controlled process); (b) response (the measured feedback); (c) model (the mathematical description of the process); (d) adaptor (to update the parameters); and (e) controller (to determine optimum dosing strategy). In addition to the conventional distinction between open-loop and closed-loop control systems, a classification is proposed for dosage optimisation techniques which distinguishes between tight-loop and loose-loop methods depending on whether physician's interaction is absent or included as part of the control step. Unlike engineering problems where the process can usually be controlled by fully automated devices, therapeutic situations often require that the physician be included in the decision-making process to determine the 'optimal' dosing strategy. Tight-loop and loose-loop methods can be further divided into adaptive and non-adaptive, depending on the presence of the adaptor. The main application areas of tight-loop feedback control methods are general anaesthesia, control of blood pressure, and insulin delivery devices. Loose-loop feedback methods have been used for oral anticoagulation and in therapeutic drug monitoring. The methodology, advantages and limitations of the different approaches are reviewed. A general feature common to all application areas could be observed: to perform well under routine clinical conditions, which are characterised by large interpatient variability and sometimes also intrapatient changes, control systems should be adaptive. Apart from application in routine drug treatment, feedback control methods represent an important research tool. They can be applied for the investigation of pathophysiological and pharmacodynamic processes. A most promising application is the evaluation of the relationship between an intermediate response (e.g. drug level), which is often used as feedback for dosage adjustment, and the final therapeutic goal.

Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

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

Schlipf, David; Raach, Steffen; Haizmann, Florian

2015-12-14

This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the predictionmore » time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.« less

Adaptive management for ecosystem services.

PubMed

Birgé, Hannah E; Allen, Craig R; Garmestani, Ahjond S; Pope, Kevin L

2016-12-01

Management of natural resources for the production of ecosystem services, which are vital for human well-being, is necessary even when there is uncertainty regarding system response to management action. This uncertainty is the result of incomplete controllability, complex internal feedbacks, and non-linearity that often interferes with desired management outcomes, and insufficient understanding of nature and people. Adaptive management was developed to reduce such uncertainty. We present a framework for the application of adaptive management for ecosystem services that explicitly accounts for cross-scale tradeoffs in the production of ecosystem services. Our framework focuses on identifying key spatiotemporal scales (plot, patch, ecosystem, landscape, and region) that encompass dominant structures and processes in the system, and includes within- and cross-scale dynamics, ecosystem service tradeoffs, and management controllability within and across scales. Resilience theory recognizes that a limited set of ecological processes in a given system regulate ecosystem services, yet our understanding of these processes is poorly understood. If management actions erode or remove these processes, the system may shift into an alternative state unlikely to support the production of desired services. Adaptive management provides a process to assess the underlying within and cross-scale tradeoffs associated with production of ecosystem services while proceeding with management designed to meet the demands of a growing human population. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hormesis and adaptive cellular control systems

EPA Science Inventory

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

A technique for improved maxillary record base adaptation through controlled polymerization of light-activated dental resins.

PubMed

Hopkins, D S; Phoenix, R D; Abrahamsen, T C

1997-09-01

A technique for the fabrication of light-activated maxillary record bases is described. The use of a segmental polymerization process provides improved palatal adaptation by minimizing the effects of polymerization shrinkage. Utilization of this technique results in record bases that are well adapted to the corresponding master casts.

Adaptation to Emotional Conflict: Evidence from a Novel Face Emotion Paradigm

PubMed Central

Clayson, Peter E.; Larson, Michael J.

2013-01-01

The preponderance of research on trial-by-trial recruitment of affective control (e.g., conflict adaptation) relies on stimuli wherein lexical word information conflicts with facial affective stimulus properties (e.g., the face-Stroop paradigm where an emotional word is overlaid on a facial expression). Several studies, however, indicate different neural time course and properties for processing of affective lexical stimuli versus affective facial stimuli. The current investigation used a novel task to examine control processes implemented following conflicting emotional stimuli with conflict-inducing affective face stimuli in the absence of affective words. Forty-one individuals completed a task wherein the affective-valence of the eyes and mouth were either congruent (happy eyes, happy mouth) or incongruent (happy eyes, angry mouth) while high-density event-related potentials (ERPs) were recorded. There was a significant congruency effect and significant conflict adaptation effects for error rates. Although response times (RTs) showed a significant congruency effect, the effect of previous-trial congruency on current-trial RTs was only present for current congruent trials. Temporospatial principal components analysis showed a P3-like ERP source localized using FieldTrip software to the medial cingulate gyrus that was smaller on incongruent than congruent trials and was significantly influenced by the recruitment of control processes following previous-trial emotional conflict (i.e., there was significant conflict adaptation in the ERPs). Results show that a face-only paradigm may be sufficient to elicit emotional conflict and suggest a system for rapidly detecting conflicting emotional stimuli and subsequently adjusting control resources, similar to cognitive conflict detection processes, when using conflicting facial expressions without words. PMID:24073278

Adaptation to emotional conflict: evidence from a novel face emotion paradigm.

PubMed

Clayson, Peter E; Larson, Michael J

2013-01-01

The preponderance of research on trial-by-trial recruitment of affective control (e.g., conflict adaptation) relies on stimuli wherein lexical word information conflicts with facial affective stimulus properties (e.g., the face-Stroop paradigm where an emotional word is overlaid on a facial expression). Several studies, however, indicate different neural time course and properties for processing of affective lexical stimuli versus affective facial stimuli. The current investigation used a novel task to examine control processes implemented following conflicting emotional stimuli with conflict-inducing affective face stimuli in the absence of affective words. Forty-one individuals completed a task wherein the affective-valence of the eyes and mouth were either congruent (happy eyes, happy mouth) or incongruent (happy eyes, angry mouth) while high-density event-related potentials (ERPs) were recorded. There was a significant congruency effect and significant conflict adaptation effects for error rates. Although response times (RTs) showed a significant congruency effect, the effect of previous-trial congruency on current-trial RTs was only present for current congruent trials. Temporospatial principal components analysis showed a P3-like ERP source localized using FieldTrip software to the medial cingulate gyrus that was smaller on incongruent than congruent trials and was significantly influenced by the recruitment of control processes following previous-trial emotional conflict (i.e., there was significant conflict adaptation in the ERPs). Results show that a face-only paradigm may be sufficient to elicit emotional conflict and suggest a system for rapidly detecting conflicting emotional stimuli and subsequently adjusting control resources, similar to cognitive conflict detection processes, when using conflicting facial expressions without words.

Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)

DTIC Science & Technology

2007-04-01

weight will be reduced by replacing heavy harness assemblies and FADECs , with distributed processing elements interconnected. This paper reviews...Digital Electronic Controls ( FADECs ), with distributed processing elements interconnected through a serial bus. Efficient data flow throughout the...because intelligence is embedded in components while overall control is maintained in the FADEC . The need for Distributed Control Systems in

Active Inference, homeostatic regulation and adaptive behavioural control

PubMed Central

Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

2015-01-01

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

Accounting for sequential trial effects in the flanker task: conflict adaptation or associative priming?

PubMed

Nieuwenhuis, Sander; Stins, John F; Posthuma, Danielle; Polderman, Tinca J C; Boomsma, Dorret I; de Geus, Eco J

2006-09-01

The conflict-control loop theory proposes that the detection of conflict in information processing triggers an increase in cognitive control, resulting in improved performance on the subsequent trial. This theory seems consistent with the robust finding that conflict susceptibility is reduced following correct trials associated with high conflict: the conflict adaptation effect. However, despite providing favorable conditions for eliciting and detecting conflict-triggered performance adjustments, none of the five experiments reported here provide unequivocal evidence of such adjustments. Instead, the results corroborate and extend earlier findings by demonstrating that the conflict adaptation effect, at least in the flanker task, is only present for a specific subset of trial sequences that is characterized by a response repetition. This pattern of results provides strong evidence that the conflict adaptation effect reflects associative stimulus-response priming instead of conflict-driven adaptations in cognitive control.

Development of a Voice Activity Controlled Noise Canceller

PubMed Central

Abid Noor, Ali O.; Samad, Salina Abdul; Hussain, Aini

2012-01-01

In this paper, a variable threshold voice activity detector (VAD) is developed to control the operation of a two-sensor adaptive noise canceller (ANC). The VAD prohibits the reference input of the ANC from containing some strength of actual speech signal during adaptation periods. The novelty of this approach resides in using the residual output from the noise canceller to control the decisions made by the VAD. Thresholds of full-band energy and zero-crossing features are adjusted according to the residual output of the adaptive filter. Performance evaluation of the proposed approach is quoted in terms of signal to noise ratio improvements as well mean square error (MSE) convergence of the ANC. The new approach showed an improved noise cancellation performance when tested under several types of environmental noise. Furthermore, the computational power of the adaptive process is reduced since the output of the adaptive filter is efficiently calculated only during non-speech periods. PMID:22778667

Rapid adaptive responses to climate change in corals

NASA Astrophysics Data System (ADS)

Torda, Gergely; Donelson, Jennifer M.; Aranda, Manuel; Barshis, Daniel J.; Bay, Line; Berumen, Michael L.; Bourne, David G.; Cantin, Neal; Foret, Sylvain; Matz, Mikhail; Miller, David J.; Moya, Aurelie; Putnam, Hollie M.; Ravasi, Timothy; van Oppen, Madeleine J. H.; Thurber, Rebecca Vega; Vidal-Dupiol, Jeremie; Voolstra, Christian R.; Watson, Sue-Ann; Whitelaw, Emma; Willis, Bette L.; Munday, Philip L.

2017-09-01

Pivotal to projecting the fate of coral reefs is the capacity of reef-building corals to acclimatize and adapt to climate change. Transgenerational plasticity may enable some marine organisms to acclimatize over several generations and it has been hypothesized that epigenetic processes and microbial associations might facilitate adaptive responses. However, current evidence is equivocal and understanding of the underlying processes is limited. Here, we discuss prospects for observing transgenerational plasticity in corals and the mechanisms that could enable adaptive plasticity in the coral holobiont, including the potential role of epigenetics and coral-associated microbes. Well-designed and strictly controlled experiments are needed to distinguish transgenerational plasticity from other forms of plasticity, and to elucidate the underlying mechanisms and their relative importance compared with genetic adaptation.

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera)

PubMed Central

2012-01-01

Background Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. Results We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Conclusions Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation. PMID:23021491

Correlation of proteome-wide changes with social immunity behaviors provides insight into resistance to the parasitic mite, Varroa destructor, in the honey bee (Apis mellifera).

PubMed

Parker, Robert; Guarna, M Marta; Melathopoulos, Andony P; Moon, Kyung-Mee; White, Rick; Huxter, Elizabeth; Pernal, Stephen F; Foster, Leonard J

2012-06-29

Disease is a major factor driving the evolution of many organisms. In honey bees, selection for social behavioral responses is the primary adaptive process facilitating disease resistance. One such process, hygienic behavior, enables bees to resist multiple diseases, including the damaging parasitic mite Varroa destructor. The genetic elements and biochemical factors that drive the expression of these adaptations are currently unknown. Proteomics provides a tool to identify proteins that control behavioral processes, and these proteins can be used as biomarkers to aid identification of disease tolerant colonies. We sampled a large cohort of commercial queen lineages, recording overall mite infestation, hygiene, and the specific hygienic response to V. destructor. We performed proteome-wide correlation analyses in larval integument and adult antennae, identifying several proteins highly predictive of behavior and reduced hive infestation. In the larva, response to wounding was identified as a key adaptive process leading to reduced infestation, and chitin biosynthesis and immune responses appear to represent important disease resistant adaptations. The speed of hygienic behavior may be underpinned by changes in the antenna proteome, and chemosensory and neurological processes could also provide specificity for detection of V. destructor in antennae. Our results provide, for the first time, some insight into how complex behavioural adaptations manifest in the proteome of honey bees. The most important biochemical correlations provide clues as to the underlying molecular mechanisms of social and innate immunity of honey bees. Such changes are indicative of potential divergence in processes controlling the hive-worker maturation.

Trichinella spiralis: the evolution of adaptation and parasitism

USDA-ARS?s Scientific Manuscript database

Parasitism among nematodes has occurred in multiple, independent events. Deciphering processes that drive species diversity and adaptation are keys to understanding parasitism and advancing control strategies. Studies have been put forth on morphological and physiological aspects of parasitism and a...

Model-free adaptive control of advanced power plants

DOEpatents

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

2015-08-18

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

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

Dream controller

DOEpatents

Cheng, George Shu-Xing; Mulkey, Steven L; Wang, Qiang; Chow, Andrew J

2013-11-26

A method and apparatus for intelligently controlling continuous process variables. A Dream Controller comprises an Intelligent Engine mechanism and a number of Model-Free Adaptive (MFA) controllers, each of which is suitable to control a process with specific behaviors. The Intelligent Engine can automatically select the appropriate MFA controller and its parameters so that the Dream Controller can be easily used by people with limited control experience and those who do not have the time to commission, tune, and maintain automatic controllers.

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

Performance optimization of PM-16QAM transmission system enabled by real-time self-adaptive coding.

PubMed

Qu, Zhen; Li, Yao; Mo, Weiyang; Yang, Mingwei; Zhu, Shengxiang; Kilper, Daniel C; Djordjevic, Ivan B

2017-10-15

We experimentally demonstrate self-adaptive coded 5×100  Gb/s WDM polarization multiplexed 16 quadrature amplitude modulation transmission over a 100 km fiber link, which is enabled by a real-time control plane. The real-time optical signal-to-noise ratio (OSNR) is measured using an optical performance monitoring device. The OSNR measurement is processed and fed back using control plane logic and messaging to the transmitter side for code adaptation, where the binary data are adaptively encoded with three types of low-density parity-check (LDPC) codes with code rates of 0.8, 0.75, and 0.7 of large girth. The total code-adaptation latency is measured to be 2273 ms. Compared with transmission without adaptation, average net capacity improvements of 102%, 36%, and 7.5% are obtained, respectively, by adaptive LDPC coding.

An adaptive deep-coupled GNSS/INS navigation system with hybrid pre-filter processing

NASA Astrophysics Data System (ADS)

Wu, Mouyan; Ding, Jicheng; Zhao, Lin; Kang, Yingyao; Luo, Zhibin

2018-02-01

The deep-coupling of a global navigation satellite system (GNSS) with an inertial navigation system (INS) can provide accurate and reliable navigation information. There are several kinds of deeply-coupled structures. These can be divided mainly into coherent and non-coherent pre-filter based structures, which have their own strong advantages and disadvantages, especially in accuracy and robustness. In this paper, the existing pre-filters of the deeply-coupled structures are analyzed and modified to improve them firstly. Then, an adaptive GNSS/INS deeply-coupled algorithm with hybrid pre-filters processing is proposed to combine the advantages of coherent and non-coherent structures. An adaptive hysteresis controller is designed to implement the hybrid pre-filters processing strategy. The simulation and vehicle test results show that the adaptive deeply-coupled algorithm with hybrid pre-filters processing can effectively improve navigation accuracy and robustness, especially in a GNSS-challenged environment.

Adaptive control of nonlinear system using online error minimum neural networks.

PubMed

Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

2016-11-01

In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-09-01

This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Simulation to coating weight control for galvanizing

NASA Astrophysics Data System (ADS)

Wang, Junsheng; Yan, Zhang; Wu, Kunkui; Song, Lei

2013-05-01

Zinc coating weight control is one of the most critical issues for continuous galvanizing line. The process has the characteristic of variable-time large time delay, nonlinear, multivariable. It can result in seriously coating weight error and non-uniform coating. We develop a control system, which can automatically control the air knives pressure and its position to give a constant and uniform zinc coating, in accordance with customer-order specification through an auto-adaptive empirical model-based feed forward adaptive controller, and two model-free adaptive feedback controllers . The proposed models with controller were applied to continuous galvanizing line (CGL) at Angang Steel Works. By the production results, the precise and stability of the control model reduces over-coating weight and improves coating uniform. The product for this hot dip galvanizing line does not only satisfy the customers' quality requirement but also save the zinc consumption.

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.

Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy.

PubMed

Miall, R Chris; Kitchen, Nick M; Nam, Se-Ho; Lefumat, Hannah; Renault, Alix G; Ørstavik, Kristin; Cole, Jonathan D; Sarlegna, Fabrice R

2018-05-19

It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participants' perception of applied forces. With visual feedback, the PL participants could report the perturbation's direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies.

Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

NASA Astrophysics Data System (ADS)

Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

2018-02-01

In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

Adaptive management for subsurface pressure and plume control in application to geological CO2 storage

NASA Astrophysics Data System (ADS)

Gonzalez-Nicolas, A.; Cihan, A.; Birkholzer, J. T.; Petrusak, R.; Zhou, Q.; Riestenberg, D. E.; Trautz, R. C.; Godec, M.

2016-12-01

Industrial-scale injection of CO2 into the subsurface can cause reservoir pressure increases that must be properly controlled to prevent any potential environmental impact. Excessive pressure buildup in reservoir may result in ground water contamination stemming from leakage through conductive pathways, such as improperly plugged abandoned wells or distant faults, and the potential for fault reactivation and possibly seal breaching. Brine extraction is a viable approach for managing formation pressure, effective stress, and plume movement during industrial-scale CO2 injection projects. The main objectives of this study are to investigate suitable different pressure management strategies involving active brine extraction and passive pressure relief wells. Adaptive optimized management of CO2 storage projects utilizes the advanced automated optimization algorithms and suitable process models. The adaptive management integrates monitoring, forward modeling, inversion modeling and optimization through an iterative process. In this study, we employ an adaptive framework to understand primarily the effects of initial site characterization and frequency of the model update (calibration) and optimization calculations for controlling extraction rates based on the monitoring data on the accuracy and the success of the management without violating pressure buildup constraints in the subsurface reservoir system. We will present results of applying the adaptive framework to test appropriateness of different management strategies for a realistic field injection project.

Stochastic Adaptive Estimation and Control.

DTIC Science & Technology

1994-10-26

Marcus, "Language Stability and Stabilizability of Discrete Event Dynamical Systems ," SIAM Journal on Control and Optimization, 31, September 1993...in the hierarchical control of flexible manufacturing systems ; in this problem, the model involves a hybrid process in continuous time whose state is...of the average cost control problem for discrete- time Markov processes. Our exposition covers from finite to Borel state and action spaces and

Basic Research on Adaptive Model Algorithmic Control

DTIC Science & Technology

1985-12-01

Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

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.

Disentangling cognition and emotion in older adults: the role of cognitive control and mental health in emotional conflict adaptation.

PubMed

Hantke, Nathan C; Gyurak, Anett; Van Moorleghem, Katie; Waring, Jill D; Adamson, Maheen M; O'Hara, Ruth; Beaudreau, Sherry A

2017-08-01

Recent research suggests cognition has a bidirectional relationship with emotional processing in older adults, yet the relationship is still poorly understood. We aimed to examine a potential relationship between late-life cognitive function, mental health symptoms, and emotional conflict adaptation. We hypothesized that worse cognitive control abilities would be associated with poorer emotional conflict adaptation. We further hypothesized that a higher severity of mental health symptoms would be associated with poorer emotional conflict adaptation. Participants included 83 cognitively normal community-dwelling older adults who completed a targeted mental health and cognitive battery, and emotion and gender conflict-adaptation tasks. Consistent with our hypothesis, poorer performance on components of cognitive control, specifically attention and working memory, was associated with poorer emotional conflict adaptation. This association with attention and working memory was not observed in the non-affective-based gender conflict adaptation task. Mental health symptoms did not predict emotional conflict adaptation, nor did performance on other cognitive measures. Our findings suggest that emotion conflict adaptation is disrupted in older individuals who have poorer attention and working memory. Components of cognitive control may therefore be an important potential source of inter-individual differences in late-life emotion regulation and cognitive affective deficits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

NASA Technical Reports Server (NTRS)

Jacklin, Stephen; Schumann, Johann; Gupta, Pramod; Richard, Michael; Guenther, Kurt; Soares, Fola

2005-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Identification and control of a multizone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.; Singh, N. B.

1992-01-01

This paper presents an intelligent adaptive control system for the control of a solid-liquid interface of a crystal while it is growing via directional solidification inside a multizone transparent furnace. The task of the process controller is to establish a user-specified axial temperature profile and to maintain a desirable interface shape. Both single-input-single-output and multi-input-multi-output adaptive pole placement algorithms have been used to control the temperature. Also described is an intelligent measurement system to assess the shape of the crystal while it is growing. A color video imaging system observes the crystal in real time and determines the position and the shape of the interface. This information is used to evaluate the crystal growth rate, and to analyze the effects of translational velocity and temperature profiles on the shape of the interface. Creation of this knowledge base is the first step to incorporate image processing into furnace control.

Context-Sensitive Adjustment of Cognitive Control in Dual-Task Performance

ERIC Educational Resources Information Center

Fischer, Rico; Gottschalk, Caroline; Dreisbach, Gesine

2014-01-01

Performing 2 highly similar tasks at the same time requires an adaptive regulation of cognitive control to shield prioritized primary task processing from between-task (cross-talk) interference caused by secondary task processing. In the present study, the authors investigated how implicitly and explicitly delivered information promotes the…

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.

Rational metareasoning and the plasticity of cognitive control.

PubMed

Lieder, Falk; Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L

2018-04-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people's ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure.

Rational metareasoning and the plasticity of cognitive control

PubMed Central

Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L.

2018-01-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people’s ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure. PMID:29694347

Real-time laser cladding control with variable spot size

NASA Astrophysics Data System (ADS)

Arias, J. L.; Montealegre, M. A.; Vidal, F.; Rodríguez, J.; Mann, S.; Abels, P.; Motmans, F.

2014-03-01

Laser cladding processing has been used in different industries to improve the surface properties or to reconstruct damaged pieces. In order to cover areas considerably larger than the diameter of the laser beam, successive partially overlapping tracks are deposited. With no control over the process variables this conduces to an increase of the temperature, which could decrease mechanical properties of the laser cladded material. Commonly, the process is monitored and controlled by a PC using cameras, but this control suffers from a lack of speed caused by the image processing step. The aim of this work is to design and develop a FPGA-based laser cladding control system. This system is intended to modify the laser beam power according to the melt pool width, which is measured using a CMOS camera. All the control and monitoring tasks are carried out by a FPGA, taking advantage of its abundance of resources and speed of operation. The robustness of the image processing algorithm is assessed, as well as the control system performance. Laser power is decreased as substrate temperature increases, thus maintaining a constant clad width. This FPGA-based control system is integrated in an adaptive laser cladding system, which also includes an adaptive optical system that will control the laser focus distance on the fly. The whole system will constitute an efficient instrument for part repair with complex geometries and coating selective surfaces. This will be a significant step forward into the total industrial implementation of an automated industrial laser cladding process.

Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

PubMed

Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

Eating behaviour associated with differences in conflict adaptation for food pictures.

PubMed

Husted, Margaret; Banks, Adrian P; Seiss, Ellen

2016-10-01

The goal conflict model of eating (Stroebe, Mensink, Aarts, Schut, & Kruglanski, 2008) proposes differences in eating behaviour result from peoples' experience of holding conflicting goals of eating enjoyment and weight maintenance. However, little is understood about the relationship between eating behaviour and the cognitive processes involved in conflict. This study aims to investigate associations between eating behaviour traits and cognitive conflict processes, specifically the application of cognitive control when processing distracting food pictures. A flanker task using food and non-food pictures was used to examine individual differences in conflict adaptation. Participants responded to target pictures whilst ignoring distracting flanking pictures. Individual differences in eating behaviour traits, attention towards target pictures, and ability to apply cognitive control through adaptation to conflicting picture trials were analysed. Increased levels of external and emotional eating were related to slower responses to food pictures indicating food target avoidance. All participants showed greater distraction by food compared to non-food pictures. Of particular significance, increased levels of emotional eating were associated with greater conflict adaptation for conflicting food pictures only. Emotional eaters demonstrate greater application of cognitive control for conflicting food pictures as part of a food avoidance strategy. This could represent an attempt to inhibit their eating enjoyment goal in order for their weight maintenance goal to dominate. Copyright © 2016 Elsevier Ltd. All rights reserved.

The neural oscillations of conflict adaptation in the human frontal region.

PubMed

Tang, Dandan; Hu, Li; Chen, Antao

2013-07-01

Incongruency between print color and the semantic meaning of a word in a classical Stroop task activates the human conflict monitoring system and triggers a behavioral conflict. Conflict adaptation has been suggested to mediate the cortical processing of neural oscillations in such a conflict situation. However, the basic mechanisms that underlie the influence of conflict adaptation on the changes of neural oscillations are not clear. In the present study, electroencephalography (EEG) data were recorded from sixteen healthy human participants while they were performing a color-word Stroop task within a novel look-to-do transition design that included two response modalities. In the 'look' condition, participants were informed to look at the color of presented words but no responses were required; in the 'do' condition, they were informed to make arranged responses to the color of presented words. Behaviorally, a reliable conflict adaptation was observed. Time-frequency analysis revealed that (1) in the 'look' condition, theta-band activity in the left- and right-frontal regions reflected a conflict-related process at a response inhibition level; and (2) in the 'do' condition, both theta-band activity in the left-frontal region and alpha-band activity in the left-, right-, and centro-frontal regions reflected a process of conflict control, which triggered neural and behavioral adaptation. Taken together, these results suggest that there are frontal mechanisms involving neural oscillations that can mediate response inhibition processes and control behavioral conflict. Copyright © 2013 Elsevier B.V. All rights reserved.

Real-time Adaptive Control Using Neural Generalized Predictive Control

NASA Technical Reports Server (NTRS)

Haley, Pam; Soloway, Don; Gold, Brian

1999-01-01

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

Direct adaptive control of a PUMA 560 industrial robot

NASA Technical Reports Server (NTRS)

Seraji, Homayoun; Lee, Thomas; Delpech, Michel

1989-01-01

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

Exploring factors that influence the spread and sustainability of a dysphagia innovation: an instrumental case study.

PubMed

Ilott, Irene; Gerrish, Kate; Eltringham, Sabrina A; Taylor, Carolyn; Pownall, Sue

2016-08-18

Swallowing difficulties challenge patient safety due to the increased risk of malnutrition, dehydration and aspiration pneumonia. A theoretically driven study was undertaken to examine the spread and sustainability of a locally developed innovation that involved using the Inter-Professional Dysphagia Framework to structure education for the workforce. A conceptual framework with 3 spread strategies (hierarchical control, participatory adaptation and facilitated evolution) was blended with a processual approach to sustaining organisational change. The aim was to understand the processes, mechanism and outcomes associated with the spread and sustainability of this safety initiative. An instrumental case study, prospectively tracked a dysphagia innovation for 34 months (April 2011 to January 2014) in a large health care organisation in England. A train-the-trainer intervention (as participatory adaptation) was deployed on care pathways for stroke and fractured neck of femur. Data were collected at the organisational and clinical level through interviews (n = 30) and document review. The coding frame combined the processual approach with the spread mechanisms. Pre-determined outcomes included the number of staff trained about dysphagia and impact related to changes in practice. The features and processes associated with hierarchical control and participatory adaptation were identified. Leadership, critical junctures, temporality and making the innovation routine were aspects of hierarchical control. Participatory adaptation was evident on the care pathways through stakeholder responses, workload and resource pressures. Six of the 25 ward based trainers cascaded the dysphagia training. The expected outcomes were achieved when the top-down mandate (hierarchical control) was supplemented by local engagement and support (participatory adaptation). Frameworks for spread and sustainability were combined to create a 'small theory' that described the interventions, the processes and desired outcomes a priori. This novel methodological approach confirmed what is known about spread and sustainability, highlighted the particularity of change and offered new insights into the factors associated with hierarchical control and participatory adaptation. The findings illustrate the dualities of organisational change as universal and context specific; as particular and amendable to theoretical generalisation. Appreciating these dualities may contribute to understanding why many innovations fail to become routine.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Nonlinear model predictive control for chemical looping process

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

Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng

A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to amore » CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.« less

Activation of the cerebellar cortex and the dentate nucleus in a prism adaptation fMRI study.

PubMed

Küper, Michael; Wünnemann, Meret J S; Thürling, Markus; Stefanescu, Roxana M; Maderwald, Stefan; Elles, Hans G; Göricke, Sophia; Ladd, Mark E; Timmann, Dagmar

2014-04-01

During prism adaptation two types of learning processes can be distinguished. First, fast strategic motor control responses are predominant in the early course of prism adaptation to achieve rapid error correction within few trials. Second, slower spatial realignment occurs among the misaligned visual and proprioceptive sensorimotor coordinate system. The aim of the present ultra-highfield (7T) functional magnetic resonance imaging (fMRI) study was to explore cerebellar cortical and dentate nucleus activation during the course of prism adaptation in relation to a similar visuomotor task without prism exposure. Nineteen young healthy participants were included into the study. Recently developed normalization procedures were applied for the cerebellar cortex and the dentate nucleus. By means of subtraction analysis (early prism adaptation > visuomotor, early prism adaptation > late prism adaptation) we identified ipsilateral activation associated with strategic motor control responses within the posterior cerebellar cortex (lobules VIII and IX) and the ventro-caudal dentate nucleus. During the late phase of adaptation we observed pronounced activation of posterior parts of lobule VI, although subtraction analyses (late prism adaptation > visuomotor) remained negative. These results are in good accordance with the concept of a representation of non-motor functions, here strategic control, within the ventro-caudal dentate nucleus. Copyright © 2013 Wiley Periodicals, Inc.

Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants

NASA Astrophysics Data System (ADS)

Masri Husam Fayiz, Al

2017-01-01

The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms.

[Adaptation of control mechanisms involved in upright undisturbed stance maintenance during prolonged darkness].

PubMed

Rougier, P

2003-04-01

To assess to which extent the non visual somato-sensorial information may, through a recalibration process, induce a reorganisation by the central nervous system to control undisturbed upright stance. Ten healthy adults were placed in complete darkness for a 24 min period. Their postural performance was recorded through a force platform on which they were required to stand still at regular intervals. Centre of Pressure (CP) displacements, recorded from the platform, were modelled as fractional brownian motion. Through this analysis, one may objectively assess from which distance and for how long the corrective process is initiated with the aim of slowing and retrace its steps. In addition, the degree to which the CP trajectories are successively controlled was determined. Once in complete darkness, an increase of the mean time intervals (Delta(t)) before the corrective process intervenes was observed, the effect being mostly significant for the mediolateral direction. In parallel, the mean distances covered at this Delta(t) were slightly affected for both mediolateral and anteroposterior directions. Lastly, the degree to which the CP trajectories are controlled tended to decrease. These data suggest a reorganisation of the control mechanisms called into play for maintaining an undisturbed upright stance, thus implying participation of the central nervous system. This short-term adaptation is discussed on the basis of our knowledge of long term adaptations previously observed in blind individuals, and also in a rehabilitation perspective.

An intelligent CNC machine control system architecture

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

Miller, D.J.; Loucks, C.S.

1996-10-01

Intelligent, agile manufacturing relies on automated programming of digitally controlled processes. Currently, processes such as Computer Numerically Controlled (CNC) machining are difficult to automate because of highly restrictive controllers and poor software environments. It is also difficult to utilize sensors and process models for adaptive control, or to integrate machining processes with other tasks within a factory floor setting. As part of a Laboratory Directed Research and Development (LDRD) program, a CNC machine control system architecture based on object-oriented design and graphical programming has been developed to address some of these problems and to demonstrate automated agile machining applications usingmore » platform-independent software.« less

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Tian, Mingyan; Huang, Jiaqi; Zhang, Rui; Ma, Zhen

2015-09-01

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

An efficient transmission power control scheme for temperature variation in wireless sensor networks.

PubMed

Lee, Jungwook; Chung, Kwangsue

2011-01-01

Wireless sensor networks collect data from several nodes dispersed at remote sites. Sensor nodes can be installed in harsh environments such as deserts, cities, and indoors, where the link quality changes considerably over time. Particularly, changes in transmission power may be caused by temperature, humidity, and other factors. In order to compensate for link quality changes, existing schemes detect the link quality changes between nodes and control transmission power through a series of feedback processes, but these approaches can cause heavy overhead with the additional control packets needed. In this paper, the change of the link quality according to temperature is examined through empirical experimentation. A new power control scheme combining both temperature-aware link quality compensation and a closed-loop feedback process to adapt to link quality changes is proposed. We prove that the proposed scheme effectively adapts the transmission power to the changing link quality with less control overhead and energy consumption.

Designing for adaptation to novelty and change: functional information, emergent feature graphics, and higher-level control.

PubMed

Hajdukiewicz, John R; Vicente, Kim J

2002-01-01

Ecological interface design (EID) is a theoretical framework that aims to support worker adaptation to change and novelty in complex systems. Previous evaluations of EID have emphasized representativeness to enhance generalizability of results to operational settings. The research presented here is complementary, emphasizing experimental control to enhance theory building. Two experiments were conducted to test the impact of functional information and emergent feature graphics on adaptation to novelty and change in a thermal-hydraulic process control microworld. Presenting functional information in an interface using emergent features encouraged experienced participants to become perceptually coupled to the interface and thereby to exhibit higher-level control and more successful adaptation to unanticipated events. The absence of functional information or of emergent features generally led to lower-level control and less success at adaptation, the exception being a minority of participants who compensated by relying on analytical reasoning. These findings may have practical implications for shaping coordination in complex systems and fundamental implications for the development of a general unified theory of coordination for the technical, human, and social sciences. Actual or potential applications of this research include the design of human-computer interfaces that improve safety in complex sociotechnical systems.

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.

Handwritten word preprocessing for database adaptation

NASA Astrophysics Data System (ADS)

Oprean, Cristina; Likforman-Sulem, Laurence; Mokbel, Chafic

2013-01-01

Handwriting recognition systems are typically trained using publicly available databases, where data have been collected in controlled conditions (image resolution, paper background, noise level,...). Since this is not often the case in real-world scenarios, classification performance can be affected when novel data is presented to the word recognition system. To overcome this problem, we present in this paper a new approach called database adaptation. It consists of processing one set (training or test) in order to adapt it to the other set (test or training, respectively). Specifically, two kinds of preprocessing, namely stroke thickness normalization and pixel intensity normalization are considered. The advantage of such approach is that we can re-use the existing recognition system trained on controlled data. We conduct several experiments with the Rimes 2011 word database and with a real-world database. We adapt either the test set or the training set. Results show that training set adaptation achieves better results than test set adaptation, at the cost of a second training stage on the adapted data. Accuracy of data set adaptation is increased by 2% to 3% in absolute value over no adaptation.

Context Specificity of Post-Error and Post-Conflict Cognitive Control Adjustments

PubMed Central

Forster, Sarah E.; Cho, Raymond Y.

2014-01-01

There has been accumulating evidence that cognitive control can be adaptively regulated by monitoring for processing conflict as an index of online control demands. However, it is not yet known whether top-down control mechanisms respond to processing conflict in a manner specific to the operative task context or confer a more generalized benefit. While previous studies have examined the taskset-specificity of conflict adaptation effects, yielding inconsistent results, control-related performance adjustments following errors have been largely overlooked. This gap in the literature underscores recent debate as to whether post-error performance represents a strategic, control-mediated mechanism or a nonstrategic consequence of attentional orienting. In the present study, evidence of generalized control following both high conflict correct trials and errors was explored in a task-switching paradigm. Conflict adaptation effects were not found to generalize across tasksets, despite a shared response set. In contrast, post-error slowing effects were found to extend to the inactive taskset and were predictive of enhanced post-error accuracy. In addition, post-error performance adjustments were found to persist for several trials and across multiple task switches, a finding inconsistent with attentional orienting accounts of post-error slowing. These findings indicate that error-related control adjustments confer a generalized performance benefit and suggest dissociable mechanisms of post-conflict and post-error control. PMID:24603900

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

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

Adaptive Wavelet Coding Applied in a Wireless Control System.

PubMed

Gama, Felipe O S; Silveira, Luiz F Q; Salazar, Andrés O

2017-12-13

Wireless control systems can sense, control and act on the information exchanged between the wireless sensor nodes in a control loop. However, the exchanged information becomes susceptible to the degenerative effects produced by the multipath propagation. In order to minimize the destructive effects characteristic of wireless channels, several techniques have been investigated recently. Among them, wavelet coding is a good alternative for wireless communications for its robustness to the effects of multipath and its low computational complexity. This work proposes an adaptive wavelet coding whose parameters of code rate and signal constellation can vary according to the fading level and evaluates the use of this transmission system in a control loop implemented by wireless sensor nodes. The performance of the adaptive system was evaluated in terms of bit error rate (BER) versus E b / N 0 and spectral efficiency, considering a time-varying channel with flat Rayleigh fading, and in terms of processing overhead on a control system with wireless communication. The results obtained through computational simulations and experimental tests show performance gains obtained by insertion of the adaptive wavelet coding in a control loop with nodes interconnected by wireless link. These results enable the use of this technique in a wireless link control loop.

UCP2 regulates mitochondrial fission and ventromedial nucleus control of glucose responsiveness

PubMed Central

Toda, Chitoku; Kim, Jung Dae; Impellizzeri, Daniela; Cuzzocrea, Salvatore; Liu, Zhong-Wu; Diano, Sabrina

2016-01-01

Summary The ventromedial nucleus of the hypothalamus (VMH) plays a critical role in regulating systemic glucose homeostasis. How neurons in this brain area adapt to the changing metabolic environment to regulate circulating glucose levels is ill-defined. Here we show that glucose load results in mitochondrial fission and reduced reactive oxygen species in VMH neurons mediated by dynamin-related peptide 1 (DRP1) under the control of uncoupling protein 2 (UCP2). Probed by genetic manipulations and chemical-genetic control of VMH neuronal circuitry, we unmasked that this mitochondrial adaptation determines the size of the pool of glucose-excited neurons in the VMH, and, that this process regulates systemic glucose homoeostasis. Thus, our data unmasked a critical cellular biological process controlled by mitochondrial dynamics in VMH regulation of systemic glucose homeostasis. PMID:26919426

UCP2 Regulates Mitochondrial Fission and Ventromedial Nucleus Control of Glucose Responsiveness.

PubMed

Toda, Chitoku; Kim, Jung Dae; Impellizzeri, Daniela; Cuzzocrea, Salvatore; Liu, Zhong-Wu; Diano, Sabrina

2016-02-25

The ventromedial nucleus of the hypothalamus (VMH) plays a critical role in regulating systemic glucose homeostasis. How neurons in this brain area adapt to the changing metabolic environment to regulate circulating glucose levels is ill defined. Here, we show that glucose load results in mitochondrial fission and reduced reactive oxygen species in VMH neurons mediated by dynamin-related peptide 1 (DRP1) under the control of uncoupling protein 2 (UCP2). Probed by genetic manipulations and chemical-genetic control of VMH neuronal circuitry, we unmasked that this mitochondrial adaptation determines the size of the pool of glucose-excited neurons in the VMH and that this process regulates systemic glucose homeostasis. Thus, our data unmasked a critical cellular biological process controlled by mitochondrial dynamics in VMH regulation of systemic glucose homeostasis. Copyright © 2016 Elsevier Inc. All rights reserved.

Active Inference, homeostatic regulation and adaptive behavioural control.

PubMed

Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

2015-11-01

We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

An on-line equivalent system identification scheme for adaptive control. Ph.D. Thesis - Stanford Univ.

NASA Technical Reports Server (NTRS)

Sliwa, S. M.

1984-01-01

A prime obstacle to the widespread use of adaptive control is the degradation of performance and possible instability resulting from the presence of unmodeled dynamics. The approach taken is to explicitly include the unstructured model uncertainty in the output error identification algorithm. The order of the compensator is successively increased by including identified modes. During this model building stage, heuristic rules are used to test for convergence prior to designing compensators. Additionally, the recursive identification algorithm as extended to multi-input, multi-output systems. Enhancements were also made to reduce the computational burden of an algorithm for obtaining minimal state space realizations from the inexact, multivariate transfer functions which result from the identification process. A number of potential adaptive control applications for this approach are illustrated using computer simulations. Results indicated that when speed of adaptation and plant stability are not critical, the proposed schemes converge to enhance system performance.

Adaptive control of large space structures using recursive lattice filters

NASA Technical Reports Server (NTRS)

Goglia, G. L.

1985-01-01

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

Neural networks for simultaneous classification and parameter estimation in musical instrument control

NASA Astrophysics Data System (ADS)

Lee, Michael; Freed, Adrian; Wessel, David

1992-08-01

In this report we present our tools for prototyping adaptive user interfaces in the context of real-time musical instrument control. Characteristic of most human communication is the simultaneous use of classified events and estimated parameters. We have integrated a neural network object into the MAX language to explore adaptive user interfaces that considers these facets of human communication. By placing the neural processing in the context of a flexible real-time musical programming environment, we can rapidly prototype experiments on applications of adaptive interfaces and learning systems to musical problems. We have trained networks to recognize gestures from a Mathews radio baton, Nintendo Power GloveTM, and MIDI keyboard gestural input devices. In one experiment, a network successfully extracted classification and attribute data from gestural contours transduced by a continuous space controller, suggesting their application in the interpretation of conducting gestures and musical instrument control. We discuss network architectures, low-level features extracted for the networks to operate on, training methods, and musical applications of adaptive techniques.

Effects of External Loads on Human Head Movement Control Systems

NASA Technical Reports Server (NTRS)

Nam, M. H.; Choi, O. M.

1984-01-01

The central and reflexive control strategies underlying movements were elucidated by studying the effects of external loads on human head movement control systems. Some experimental results are presented on dynamic changes weigh the addition of aviation helmet (SPH4) and lead weights (6 kg). Intended time-optimal movements, their dynamics and electromyographic activity of neck muscles in normal movements, and also in movements made with external weights applied to the head were measured. It was observed that, when the external loads were added, the subject went through complex adapting processes and the head movement trajectory and its derivatives reached steady conditions only after transient adapting period. The steady adapted state was reached after 15 to 20 seconds (i.e., 5 to 6 movements).

Dual RBFNNs-Based Model-Free Adaptive Control With Aspen HYSYS Simulation.

PubMed

Zhu, Yuanming; Hou, Zhongsheng; Qian, Feng; Du, Wenli

2017-03-01

In this brief, we propose a new data-driven model-free adaptive control (MFAC) method with dual radial basis function neural networks (RBFNNs) for a class of discrete-time nonlinear systems. The main novelty lies in that it provides a systematic design method for controller structure by the direct usage of I/O data, rather than using the first-principle model or offline identified plant model. The controller structure is determined by equivalent-dynamic-linearization representation of the ideal nonlinear controller, and the controller parameters are tuned by the pseudogradient information extracted from the I/O data of the plant, which can deal with the unknown nonlinear system. The stability of the closed-loop control system and the stability of the training process for RBFNNs are guaranteed by rigorous theoretical analysis. Meanwhile, the effectiveness and the applicability of the proposed method are further demonstrated by the numerical example and Aspen HYSYS simulation of distillation column in crude styrene produce process.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Coping with Chronic Illness in Childhood and Adolescence

PubMed Central

Compas, Bruce E.; Jaser, Sarah S.; Dunn, Madeleine J.; Rodriguez, Erin M.

2012-01-01

Chronic illnesses and medical conditions present millions of children and adolescents with significant stress that is associated with risk for emotional and behavioral problems and interferes with adherence to treatment regimens. We review research on the role of child and adolescent coping with stress as an important feature of the process of adaptation to illness. Recent findings support a control-based model of coping that includes primary control or active coping (efforts to act on the source of stress or one’s emotions), secondary control or accommodative coping (efforts to adapt to the source of stress), and disengagement or passive coping (efforts to avoid or deny the stressor). Evidence suggests the efficacy of secondary control coping in successful adaptation to chronic illness in children and adolescents, disengagement coping is associated with poorer adjustment, and findings for primary control coping are mixed. Avenues for future research are highlighted. PMID:22224836

Advanced controls for light sources

NASA Astrophysics Data System (ADS)

Biedron, S. G.; Edelen, A. L.; Milton, S. V.

2016-09-01

We present a summary of our team's recent efforts in developing adaptive, artificial intelligence-inspired techniques specifically to address several control challenges that arise in machines/systems including those in particle accelerator systems. These techniques can readily be adapted to other systems such as lasers, beamline optics, etc… We are not at all suggesting that we create an autonomous system, but create a system with an intelligent control system, that can continually use operational data to improve itself and combines both traditional and advanced techniques. We believe that the system performance and reliability can be increased based on our findings. Another related point is that the controls sub-system of an overall system is usually not the heart of the system architecture or design process. More bluntly, often times all of the peripheral systems are considered as secondary to the main system components in the architecture design process because it is assumed that the controls system will be able to "fix" challenges found later with the sub-systems for overall system operation. We will show that this is not always the case and that it took an intelligent control application to overcome a sub-system's challenges. We will provide a recent example of such a "fix" with a standard controller and with an artificial intelligence-inspired controller. A final related point to be covered is that of system adaptation for requirements not original to a system's original design.

Adaptive response due to changes in gene regulation: a study with Drosophila.

PubMed Central

McDonald, J F; Chambers, G K; David, J; Ayala, F J

1977-01-01

In spite of the critical role of the process of adaptation in evolution, there are few detailed studies of the genotypic and molecular basis of the process. Drosophila melanogaster flies selected for increased tolerance to ethanol exhibited higher levels of alcohol dehydrogenase (alcohol:NAD+ oxidoreductase; EC 1.1.1.1) activity than unselected controls. A series of tests (electrophoresis, product inhibition, temperature stability, pH optima, substrate specificity, and Michaelis constants) gave no evidence of structural differences in the enzyme of the selected and the control flies. However, quantitative immunological assays showed that the selected flies contained significantly higher amounts of alcohol dehydrogenase. Adaptation of the selected flies to higher alcohol tolerance has most likely taken place by changes not in the structural gene locus coding for the enzyme, but by regulatory changes affecting the amount of gene product. Images PMID:412190

Quality Control Barriers in Adapting "Metro-Centric" Education to Regional Needs

ERIC Educational Resources Information Center

Nagy, Judy; Robinson, Susan R.

2013-01-01

The massification and globalization of higher education, combined with the widespread adoption of processes underpinning accreditation and quality control of university programs, have tended to result in learning contexts that are increasingly narrowly conceived and tightly controlled. Underlying many quality control measures is a "one size…

[Programme for improving emotional and cognitive changes in patients under renal dialysis in Egypt].

PubMed

Awadalla, Hala I; El-Ateek, Ahmed M; Elhammady, Mohamed M; Kamel, Magda A

2008-01-01

We investigated the effect of chronic renal failure on the emotional status, social and psychological adaptation and the cognitive status of patients and the effect of a programme to improve the psychosocial state of the patients; 40 renal dialysis patients and 40 healthy controls were included. We used the Emotional Status Scale, Psychosocial Adaptation Scale, the Primary Mental Abilities Test and the Memory Processes Scale for assessment of the participants. The controls had better emotional/cognitive status and psychosocial adaptation than the dialysis patients, a statistically significant difference. There were also statistically significant differences between the patients before and after the application of the programme.

Design of adaptive control systems by means of self-adjusting transversal filters

NASA Technical Reports Server (NTRS)

Merhav, S. J.

1986-01-01

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

Timeline of Intestinal Adaptation After Malabsortive Surgery: Effect of Luminal Nutrients, Biliopancreatic Secretion, and Glutamine Supplementation.

PubMed

Martínez Moreno, José Manuel; Reyes-Ortiz, Alexander; Lage Sánchez, José María; Sánchez-Gallegos, Pilar; Garcia-Caballero, Manuel

2017-12-01

The aim of this study was to study the process of intestinal adaptation in the three limbs of the small intestine after malabsorptive bariatric surgery: the biliopancreatic limb, the alimentary limb, and the common channel. These limbs are exposed to different stimuli, namely, gastrointestinal transit and nutrients in the alimentary limb, biliopancreatic secretions in the biliopancreatic limb, and a mix of both in the common channel. We also wished to investigate the effect of glutamine supplementation on the adaptation process. Three types of surgery were performed using a porcine model: biliopancreatic bypass (BPBP), massive (75%) short bowel resection as the positive control, and a sham operation (transection) as the negative control. We measured the height and width of intestinal villi, histidine decarboxylase (HDC) activity, and amount of HDC messenger RNA (mRNA) (standard diet or a diet supplemented with glutamine). An increase in HDC activity and mRNA expression was observed in the BPBP group. This increase coincided with an increase in the height and width of the intestinal villi. The increase in villus height was observed immediately after surgery and peaked at 2 weeks. Levels remained higher than those observed in sham-operated pigs for a further 4 weeks. The intestinal adaptation process in animals that underwent BPBP was less intense than in those that underwent massive short bowel resection and more intense than in those that underwent transection only. Supplementation with glutamine did not improve any of the parameters studied, although it did appear to accelerate the adaptive process.

Cerebellar subjects show impaired adaptation of anticipatory EMG during catching.

PubMed

Lang, C E; Bastian, A J

1999-11-01

We evaluated the role of the cerebellum in adapting anticipatory muscle activity during a multijointed catching task. Individuals with and without cerebellar damage caught a series of balls of different weights dropped from above. In Experiment 1 (light-heavy-light), each subject was required to catch light balls (baseline phase), heavy balls (adaptation phase), and then light balls again (postadaptation phase). Subjects were not told when the balls would be switched, and they were required to keep their hand within a vertical spatial "window" during the catch. During the series of trials, we measured three-dimensional (3-D) position and electromyogram (EMG) from the catching arm. We modeled the adaptation process using an exponential decay function; this model allowed us to dissociate adaptation from performance variability. Results from the position data show that cerebellar subjects did not adapt or adapted very slowly to the changed ball weight when compared with the control subjects. The cerebellar group required an average of 30.9 +/- 8.7 trials (mean +/- SE) to progress approximately two-thirds of the way through the adaptation compared with 1.7 +/- 0.2 trials for the control group. Only control subjects showed a negative aftereffect indicating storage of the adaptation. No difference in performance variability existed between the two groups. EMG data show that control subjects increased their anticipatory muscle activity in the flexor muscles of the arm to control the momentum of the ball at impact. Cerebellar subjects were unable to differentially increase the anticipatory muscle activity across three joints to perform the task successfully. In Experiment 2 (heavy-light-heavy), we tested to see whether the rate of adaptation changed when adapting to a light ball versus a heavy ball. Subjects caught the heavy balls (baseline phase), the light balls (adaptation phase), and then heavy balls again (postadaptation phase). Comparison of rates of adaptation between Experiment 1 and Experiment 2 showed that the rate of adaptation was unchanged whether adapting to a light ball or a heavy ball. Given these findings, we conclude that the cerebellum is important in generating the appropriate anticipatory muscle activity across multiple muscles and modifying it in response to changing demands though trial-and-error practice.

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

PubMed

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

2015-07-24

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

Mechanisms mediating parallel action monitoring in fronto-striatal circuits.

PubMed

Beste, Christian; Ness, Vanessa; Lukas, Carsten; Hoffmann, Rainer; Stüwe, Sven; Falkenstein, Michael; Saft, Carsten

2012-08-01

Flexible response adaptation and the control of conflicting information play a pivotal role in daily life. Yet, little is known about the neuronal mechanisms mediating parallel control of these processes. We examined these mechanisms using a multi-methodological approach that integrated data from event-related potentials (ERPs) with structural MRI data and source localisation using sLORETA. Moreover, we calculated evoked wavelet oscillations. We applied this multi-methodological approach in healthy subjects and patients in a prodromal phase of a major basal ganglia disorder (i.e., Huntington's disease), to directly focus on fronto-striatal networks. Behavioural data indicated, especially the parallel execution of conflict monitoring and flexible response adaptation was modulated across the examined cohorts. When both processes do not co-incide a high integrity of fronto-striatal loops seems to be dispensable. The neurophysiological data suggests that conflict monitoring (reflected by the N2 ERP) and working memory processes (reflected by the P3 ERP) differentially contribute to this pattern of results. Flexible response adaptation under the constraint of high conflict processing affected the N2 and P3 ERP, as well as their delta frequency band oscillations. Yet, modulatory effects were strongest for the N2 ERP and evoked wavelet oscillations in this time range. The N2 ERPs were localized in the anterior cingulate cortex (BA32, BA24). Modulations of the P3 ERP were localized in parietal areas (BA7). In addition, MRI-determined caudate head volume predicted modulations in conflict monitoring, but not working memory processes. The results show how parallel conflict monitoring and flexible adaptation of action is mediated via fronto-striatal networks. While both, response monitoring and working memory processes seem to play a role, especially response selection processes and ACC-basal ganglia networks seem to be the driving force in mediating parallel conflict monitoring and flexible adaptation of actions. Copyright © 2012 Elsevier Inc. All rights reserved.

Conflict Adaptation and Congruency Sequence Effects to Social-Emotional Stimuli in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Worsham, Whitney; Gray, Whitney E.; Larson, Michael J.; South, Mikle

2015-01-01

Background: The modification of performance following conflict can be measured using conflict adaptation tasks thought to measure the change in the allocation of cognitive resources in order to reduce conflict interference and improve performance. While previous studies have suggested atypical processing during nonsocial cognitive control tasks,…

Active Hearing Mechanisms Inspire Adaptive Amplification in an Acoustic Sensor System.

PubMed

Guerreiro, Jose; Reid, Andrew; Jackson, Joseph C; Windmill, James F C

2018-06-01

Over many millions of years of evolution, nature has developed some of the most adaptable sensors and sensory systems possible, capable of sensing, conditioning and processing signals in a very power- and size-effective manner. By looking into biological sensors and systems as a source of inspiration, this paper presents the study of a bioinspired concept of signal processing at the sensor level. By exploiting a feedback control mechanism between a front-end acoustic receiver and back-end neuronal based computation, a nonlinear amplification with hysteretic behavior is created. Moreover, the transient response of the front-end acoustic receiver can also be controlled and enhanced. A theoretical model is proposed and the concept is prototyped experimentally through an embedded system setup that can provide dynamic adaptations of a sensory system comprising a MEMS microphone placed in a closed-loop feedback system. It faithfully mimics the mosquito's active hearing response as a function of the input sound intensity. This is an adaptive acoustic sensor system concept that can be exploited by sensor and system designers within acoustics and ultrasonic engineering fields.

Dynamic goal states: adjusting cognitive control without conflict monitoring.

PubMed

Scherbaum, Stefan; Dshemuchadse, Maja; Ruge, Hannes; Goschke, Thomas

2012-10-15

A central topic in the cognitive sciences is how cognitive control is adjusted flexibly to changing environmental demands at different time scales to produce goal-oriented behavior. According to an influential account, the context-sensitive recruitment of cognitive control is mediated by a specialized conflict monitoring process that registers current conflict and signals the demand for enhanced control in subsequent trials. This view has been immensely successful not least due to supporting evidence from neuroimaging studies suggesting that the conflict monitoring function is localized within the anterior cingulate cortex (ACC) which, in turn, signals the demand for enhanced control to the prefrontal cortex (PFC). In this article, we propose an alternative model of the adaptive regulation of cognitive control based on multistable goal attractor network dynamics and adjustments of cognitive control within a conflict trial. Without incorporation of an explicit conflict monitoring module, the model mirrors behavior in conflict tasks accounting for effects of response congruency, sequential conflict adaptation, and proportion of incongruent trials. Importantly, the model also mirrors frequency tagged EEG data indicating continuous conflict adaptation and suggests a reinterpretation of the correlation between ACC and the PFC BOLD data reported in previous imaging studies. Together, our simulation data propose an alternative interpretation of both behavioral data as well as imaging data that have previously been interpreted in favor of a specialized conflict monitoring process in the ACC. Copyright © 2012 Elsevier Inc. All rights reserved.

Live interactive computer music performance practice

NASA Astrophysics Data System (ADS)

Wessel, David

2002-05-01

A live-performance musical instrument can be assembled around current lap-top computer technology. One adds a controller such as a keyboard or other gestural input device, a sound diffusion system, some form of connectivity processor(s) providing for audio I/O and gestural controller input, and reactive real-time native signal processing software. A system consisting of a hand gesture controller; software for gesture analysis and mapping, machine listening, composition, and sound synthesis; and a controllable radiation pattern loudspeaker are described. Interactivity begins in the set up wherein the speaker-room combination is tuned with an LMS procedure. This system was designed for improvisation. It is argued that software suitable for carrying out an improvised musical dialog with another performer poses special challenges. The processes underlying the generation of musical material must be very adaptable, capable of rapid changes in musical direction. Machine listening techniques are used to help the performer adapt to new contexts. Machine learning can play an important role in the development of such systems. In the end, as with any musical instrument, human skill is essential. Practice is required not only for the development of musically appropriate human motor programs but for the adaptation of the computer-based instrument as well.

Multiple Concurrent Visual-Motor Mappings: Implications for Models of Adaptation

NASA Technical Reports Server (NTRS)

Cunningham, H. A.; Welch, Robert B.

1994-01-01

Previous research on adaptation to visual-motor rearrangement suggests that the central nervous system represents accurately only 1 visual-motor mapping at a time. This idea was examined in 3 experiments where subjects tracked a moving target under repeated alternations between 2 initially interfering mappings (the 'normal' mapping characteristic of computer input devices and a 108' rotation of the normal mapping). Alternation between the 2 mappings led to significant reduction in error under the rotated mapping and significant reduction in the adaptation aftereffect ordinarily caused by switching between mappings. Color as a discriminative cue, interference versus decay in adaptation aftereffect, and intermanual transfer were also examined. The results reveal a capacity for multiple concurrent visual-motor mappings, possibly controlled by a parametric process near the motor output stage of processing.

Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

PubMed

Zhang, Jianhua; Yin, Zhong; Wang, Rubin

2017-01-01

This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

Flight control actuation system

NASA Technical Reports Server (NTRS)

Wingett, Paul T. (Inventor); Gaines, Louie T. (Inventor); Evans, Paul S. (Inventor); Kern, James I. (Inventor)

2004-01-01

A flight control actuation system comprises a controller, electromechanical actuator and a pneumatic actuator. During normal operation, only the electromechanical actuator is needed to operate a flight control surface. When the electromechanical actuator load level exceeds 40 amps positive, the controller activates the pneumatic actuator to offset electromechanical actuator loads to assist the manipulation of flight control surfaces. The assistance from the pneumatic load assist actuator enables the use of an electromechanical actuator that is smaller in size and mass, requires less power, needs less cooling processes, achieves high output forces and adapts to electrical current variations. The flight control actuation system is adapted for aircraft, spacecraft, missiles, and other flight vehicles, especially flight vehicles that are large in size and travel at high velocities.

Flight control actuation system

NASA Technical Reports Server (NTRS)

Wingett, Paul T. (Inventor); Gaines, Louie T. (Inventor); Evans, Paul S. (Inventor); Kern, James I. (Inventor)

2006-01-01

A flight control actuation system comprises a controller, electromechanical actuator and a pneumatic actuator. During normal operation, only the electromechanical actuator is needed to operate a flight control surface. When the electromechanical actuator load level exceeds 40 amps positive, the controller activates the pneumatic actuator to offset electromechanical actuator loads to assist the manipulation of flight control surfaces. The assistance from the pneumatic load assist actuator enables the use of an electromechanical actuator that is smaller in size and mass, requires less power, needs less cooling processes, achieves high output forces and adapts to electrical current variations. The flight control actuation system is adapted for aircraft, spacecraft, missiles, and other flight vehicles, especially flight vehicles that are large in size and travel at high velocities.

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Development of a scalable generic platform for adaptive optics real time control

NASA Astrophysics Data System (ADS)

Surendran, Avinash; Burse, Mahesh P.; Ramaprakash, A. N.; Parihar, Padmakar

2015-06-01

The main objective of the present project is to explore the viability of an adaptive optics control system based exclusively on Field Programmable Gate Arrays (FPGAs), making strong use of their parallel processing capability. In an Adaptive Optics (AO) system, the generation of the Deformable Mirror (DM) control voltages from the Wavefront Sensor (WFS) measurements is usually through the multiplication of the wavefront slopes with a predetermined reconstructor matrix. The ability to access several hundred hard multipliers and memories concurrently in an FPGA allows performance far beyond that of a modern CPU or GPU for tasks with a well-defined structure such as Adaptive Optics control. The target of the current project is to generate a signal for a real time wavefront correction, from the signals coming from a Wavefront Sensor, wherein the system would be flexible to accommodate all the current Wavefront Sensing techniques and also the different methods which are used for wavefront compensation. The system should also accommodate for different data transmission protocols (like Ethernet, USB, IEEE 1394 etc.) for transmitting data to and from the FPGA device, thus providing a more flexible platform for Adaptive Optics control. Preliminary simulation results for the formulation of the platform, and a design of a fully scalable slope computer is presented.

The research on visual industrial robot which adopts fuzzy PID control algorithm

NASA Astrophysics Data System (ADS)

Feng, Yifei; Lu, Guoping; Yue, Lulin; Jiang, Weifeng; Zhang, Ye

2017-03-01

The control system of six degrees of freedom visual industrial robot based on the control mode of multi-axis motion control cards and PC was researched. For the variable, non-linear characteristics of industrial robot`s servo system, adaptive fuzzy PID controller was adopted. It achieved better control effort. In the vision system, a CCD camera was used to acquire signals and send them to video processing card. After processing, PC controls the six joints` motion by motion control cards. By experiment, manipulator can operate with machine tool and vision system to realize the function of grasp, process and verify. It has influence on the manufacturing of the industrial robot.

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.

Attachment, emotion regulation, and adaptation to breast cancer: assessment of a mediational hypothesis.

PubMed

Ávila, Marisa; Brandão, Tânia; Teixeira, Joana; Coimbra, Joaquim Luis; Matos, Paula Mena

2015-11-01

This study examines the links between attachment, adaptation to breast cancer, and the mediating role played by emotional regulation processes. Participants were 127 women with breast cancer recruited in two public hospitals of Porto and at the Portuguese Cancer League. Women completed measures of attachment, quality of life, and emotion regulation. Path models were used to examine the associations between the constructs and to test the mediational hypotheses. Significant associations were found between attachment and adaptation. Dimensions of emotion regulation totally or partially mediated the associations between attachment and adaptation outcomes. Attachment security effects on interpersonal relations were totally mediated by communicating emotions. Also, attachment anxiety effect on physical well-being was totally mediated by rumination. Attachment avoidance effects on psychological outcomes were totally mediated by emotional control and partially mediated by communicating emotions for the case of interpersonal relations. This study highlights the importance of addressing emotional regulation jointly with attachment to deepen the comprehension of the relational processes implicated in adaptation to breast cancer. Results supported a mediational hypothesis, presenting emotional regulation processes as relevant dimensions for the understanding of attachment associations with adaptation to breast cancer. Copyright © 2015 John Wiley & Sons, Ltd.

Encoder-Decoder Optimization for Brain-Computer Interfaces

PubMed Central

Merel, Josh; Pianto, Donald M.; Cunningham, John P.; Paninski, Liam

2015-01-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages. PMID:26029919

Encoder-decoder optimization for brain-computer interfaces.

PubMed

Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Integrated Business Process Adaptation towards Friction-Free Business-to-Business Collaboration

ERIC Educational Resources Information Center

Shan, Zhe

2011-01-01

One key issue in process-aware E-commerce collaboration is the orchestration of business processes of multiple business partners throughout a supply chain network in an automated and seamless way. Since each partner has its own internal processes with different control flow structures and message interfaces, the real challenge lies in verifying…

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The lifecycle of e-learning course in the adaptive educational environment

NASA Astrophysics Data System (ADS)

Gustun, O. N.; Budaragin, N. V.

2017-01-01

In the article we have considered the lifecycle model of the e-learning course in the electronic educational environment. This model consists of three stages and nine phases. In order to implement the adaptive control of the learning process we have determined the actions which are necessary to undertake at different phases of the e-learning course lifecycle. The general characteristics of the SPACEL-technology is given for creating adaptive educational environments of the next generation.

Adaptation, expertise, and giftedness: towards an understanding of cortical, subcortical, and cerebellar network contributions.

PubMed

Koziol, Leonard F; Budding, Deborah Ely; Chidekel, Dana

2010-12-01

Current cortico-centric models of cognition lack a cohesive neuroanatomic framework that sufficiently considers overlapping levels of function, from "pathological" through "normal" to "gifted" or exceptional ability. While most cognitive theories presume an evolutionary context, few actively consider the process of adaptation, including concepts of neurodevelopment. Further, the frequent co-occurrence of "gifted" and "pathological" function is difficult to explain from a cortico-centric point of view. This comprehensive review paper proposes a framework that includes the brain's vertical organization and considers "giftedness" from an evolutionary and neurodevelopmental vantage point. We begin by discussing the current cortico-centric model of cognition and its relationship to intelligence. We then review an integrated, dual-tiered model of cognition that better explains the process of adaptation by simultaneously allowing for both stimulus-based processing and higher-order cognitive control. We consider the role of the basal ganglia within this model, particularly in relation to reward circuitry and instrumental learning. We review the important role of white matter tracts in relation to speed of adaptation and development of behavioral mastery. We examine the cerebellum's critical role in behavioral refinement and in cognitive and behavioral automation, particularly in relation to expertise and giftedness. We conclude this integrated model of brain function by considering the savant syndrome, which we believe is best understood within the context of a dual-tiered model of cognition that allows for automaticity in adaptation as well as higher-order executive control.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

Controlling gain one photon at a time

PubMed Central

Schwartz, Gregory W; Rieke, Fred

2013-01-01

Adaptation is a salient property of sensory processing. All adaptational or gain control mechanisms face the challenge of obtaining a reliable estimate of the property of the input to be adapted to and obtaining this estimate sufficiently rapidly to be useful. Here, we explore how the primate retina balances the need to change gain rapidly and reliably when photons arrive rarely at individual rod photoreceptors. We find that the weakest backgrounds that decrease the gain of the retinal output signals are similar to those that increase human behavioral threshold, and identify a novel site of gain control in the retinal circuitry. Thus, surprisingly, the gain of retinal signals begins to decrease essentially as soon as background lights are detectable; under these conditions, gain control does not rely on a highly averaged estimate of the photon count, but instead signals from individual photon absorptions trigger changes in gain. DOI: http://dx.doi.org/10.7554/eLife.00467.001 PMID:23682314

Adaptive Working Memory Training Reduces the Negative Impact of Anxiety on Competitive Motor Performance.

PubMed

Ducrocq, Emmanuel; Wilson, Mark; Smith, Tim J; Derakshan, Nazanin

2017-12-01

Optimum levels of attentional control are essential to prevent athletes from experiencing performance breakdowns under pressure. The current study explored whether training attentional control using the adaptive dual n-back paradigm, designed to directly target processing efficiency of the main executive functions of working memory (WM), would result in transferrable effects on sports performance outcomes. A total of 30 tennis players were allocated to an adaptive WM training or active control group and underwent 10 days of training. Measures of WM capacity as well as performance and objective gaze indices of attentional control in a tennis volley task were assessed in low- and high-pressure posttraining conditions. Results revealed significant benefits of training on WM capacity, quiet eye offset, and tennis performance in the high-pressure condition. Our results confirm and extend previous findings supporting the transfer of cognitive training benefits to objective measures of sports performance under pressure.

Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming.

PubMed

Zhang, Qichao; Zhao, Dongbin; Wang, Ding

2018-01-01

In this paper, the robust control problem for a class of continuous-time nonlinear system with unmatched uncertainties is investigated using an event-based control method. First, the robust control problem is transformed into a corresponding optimal control problem with an augmented control and an appropriate cost function. Under the event-based mechanism, we prove that the solution of the optimal control problem can asymptotically stabilize the uncertain system with an adaptive triggering condition. That is, the designed event-based controller is robust to the original uncertain system. Note that the event-based controller is updated only when the triggering condition is satisfied, which can save the communication resources between the plant and the controller. Then, a single network adaptive dynamic programming structure with experience replay technique is constructed to approach the optimal control policies. The stability of the closed-loop system with the event-based control policy and the augmented control policy is analyzed using the Lyapunov approach. Furthermore, we prove that the minimal intersample time is bounded by a nonzero positive constant, which excludes Zeno behavior during the learning process. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed control scheme.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

PubMed

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

PubMed Central

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world. PMID:26528176

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A mathematical model of the creative control process is presented that illustrates the use for mobile robots. Examples from a variety of intelligent mobile robot applications are also presented. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to many applications.

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control.

PubMed

Wang, Tong; Gao, Huijun; Qiu, Jianbin

2016-02-01

This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.

Application of an Adaptive Clustering Network to Flight Control of a Fighter Aircraft. Phase 1

DTIC Science & Technology

1991-12-19

whether the underlying neurodynamics are appropriate to the dynamics of the controlled element as well as the broad objectives of the control process...Dept. of Brain & Cognitive Sciences ........................ 1 Massachusetts Institute of Technology Cambridge, MA 02139 Attn: Dr. M. Jordan Dept. of

Behind binge eating: A review of food-specific adaptations of neurocognitive and neuroimaging tasks.

PubMed

Berner, Laura A; Winter, Samantha R; Matheson, Brittany E; Benson, Leora; Lowe, Michael R

2017-07-01

Recurrent binge eating, or overeating accompanied by a sense of loss of control, is a major public health concern. Identifying similarities and differences among individuals with binge eating and those with other psychiatric symptoms and characterizing the deficits that uniquely predispose individuals to eating problems are essential to improving treatment. Research suggests that altered reward and control-related processes may contribute to dysregulated eating and other impulsive behaviors in binge-eating populations, but the best methods for reliably assessing the contributions of these processes to binge eating are unclear. In this review, we summarize standard neurocognitive and neuroimaging tasks that assess reward and control-related processes, describe adaptations of these tasks used to study eating and food-specific responsivity and deficits, and consider the advantages and limitations of these tasks. Future studies integrating both general and food-specific tasks with neuroimaging will improve understanding of the neurocognitive processes and neural circuits that contribute to binge eating and could inform novel interventions that more directly target or prevent this transdiagnostic behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

Antecedents of perceived coach interpersonal behaviors: the coaching environment and coach psychological well- and ill-being.

PubMed

Stebbings, Juliette; Taylor, Ian M; Spray, Christopher M; Ntoumanis, Nikos

2012-08-01

Embedded in the self-determination theory (Deci & Ryan, 2000) framework, we obtained self-report data from 418 paid and voluntary coaches from a variety of sports and competitive levels with the aim of exploring potential antecedents of coaches' perceived autonomy supportive and controlling behaviors. Controlling for socially desirable responses, structural equation modeling revealed that greater job security and opportunities for professional development, and lower work-life conflict were associated with psychological need satisfaction, which, in turn, was related to an adaptive process of psychological well-being and perceived autonomy support toward athletes. In contrast, higher work-life conflict and fewer opportunities for development were associated with a distinct maladaptive process of thwarted psychological needs, psychological ill-being, and perceived controlling interpersonal behavior. The results highlight how the coaching context may impact upon coaches' psychological health and their interpersonal behavior toward athletes. Moreover, evidence is provided for the independence of adaptive and maladaptive processes within the self-determination theory paradigm.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Conflict adaptation and congruency sequence effects to social-emotional stimuli in individuals with autism spectrum disorders.

PubMed

Worsham, Whitney; Gray, Whitney E; Larson, Michael J; South, Mikle

2015-11-01

The modification of performance following conflict can be measured using conflict adaptation tasks thought to measure the change in the allocation of cognitive resources in order to reduce conflict interference and improve performance. While previous studies have suggested atypical processing during nonsocial cognitive control tasks, conflict adaptation (i.e. congruency sequence effects) for social-emotional stimuli have not been previously studied in autism spectrum disorder. A total of 32 participants diagnosed with autism spectrum disorder and 27 typically developing matched controls completed an emotional Stroop conflict task that required the classification of facial affect while simultaneously ignoring an overlaid affective word. Both groups showed behavioral evidence for emotional conflict adaptation based on response times and accuracy rates. However, the autism spectrum disorder group demonstrated a speed-accuracy trade-off manifested through significantly faster response times and decreased accuracy rates on trials containing conflict between the emotional face and the overlaid emotional word. Reduced selective attention toward socially relevant information may bias individuals with autism spectrum disorder toward more rapid processing and decision making even when conflict is present. Nonetheless, the loss of important information from the social stimuli reduces decision-making accuracy, negatively affecting the ability to adapt both cognitively and emotionally when conflict arises. © The Author(s) 2014.

Distinct brain networks for adaptive and stable task control in humans

PubMed Central

Dosenbach, Nico U. F.; Fair, Damien A.; Miezin, Francis M.; Cohen, Alexander L.; Wenger, Kristin K.; Dosenbach, Ronny A. T.; Fox, Michael D.; Snyder, Abraham Z.; Vincent, Justin L.; Raichle, Marcus E.; Schlaggar, Bradley L.; Petersen, Steven E.

2007-01-01

Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms. PMID:17576922

Trends in modern system theory

NASA Technical Reports Server (NTRS)

Athans, M.

1976-01-01

The topics considered are related to linear control system design, adaptive control, failure detection, control under failure, system reliability, and large-scale systems and decentralized control. It is pointed out that the design of a linear feedback control system which regulates a process about a desirable set point or steady-state condition in the presence of disturbances is a very important problem. The linearized dynamics of the process are used for design purposes. The typical linear-quadratic design involving the solution of the optimal control problem of a linear time-invariant system with respect to a quadratic performance criterion is considered along with gain reduction theorems and the multivariable phase margin theorem. The stumbling block in many adaptive design methodologies is associated with the amount of real time computation which is necessary. Attention is also given to the desperate need to develop good theories for large-scale systems, the beginning of a microprocessor revolution, the translation of the Wiener-Hopf theory into the time domain, and advances made in dynamic team theory, dynamic stochastic games, and finite memory stochastic control.

Adaptation to recent conflict in the classical color-word Stroop-task mainly involves facilitation of processing of task-relevant information.

PubMed

Purmann, Sascha; Pollmann, Stefan

2015-01-01

To process information selectively and to continuously fine-tune selectivity of information processing are important abilities for successful goal-directed behavior. One phenomenon thought to represent this fine-tuning are conflict adaptation effects in interference tasks, i.e., reduction of interference after an incompatible trial and when incompatible trials are frequent. The neurocognitive mechanisms of these effects are currently only partly understood and results from brainimaging studies so far are mixed. In our study we validate and extend recent findings by examining adaption to recent conflict in the classical Stroop task using functional magnetic resonance imaging. Consistent with previous research we found increased activity in a fronto-parietal network comprising the medial prefrontal cortex, ventro-lateral prefrontal cortex, and posterior parietal cortex when contrasting incompatible with compatible trials. These areas have been associated with attentional processes and might reflect increased cognitive conflict and resolution thereof during incompatible trials. While carefully controlling for non-attentional sequential effects we found smaller Stroop interference after an incompatible trial (conflict adaptation effect). These behavioral conflict adaptation effects were accompanied by changes in activity in visual color-selective areas (V4, V4α), while there was no modulation by previous trial compatibility in a visual word-selective area (VWFA). Our results provide further evidence for the notion, that adaptation to recent conflict seems to be based mainly on enhancement of processing of the task-relevant information.

Conflict adaptation in schizophrenia: reviewing past and previewing future efforts.

PubMed

Abrahamse, Elger; Ruitenberg, Marit; Duthoo, Wout; Sabbe, Bernard; Morrens, Manuel; van Dijck, Jean-Philippe

2016-05-01

Cognitive control impairments have been suggested to be a critical component in the overall cognitive deficits observed in patients diagnosed with schizophrenia. Here, we zoom in on a specific function of cognitive control, conflict adaptation. Abnormal neural activity patterns have been observed for patients diagnosed with schizophrenia in core conflict adaptation areas such as anterior cingulate cortex and prefrontal cortex. On the one hand, this strongly indicates that conflict adaptation is affected. On the other hand, however, outcomes at the behavioural level are needed to create a window into a precise interpretation of this abnormal neural activity. We present a narrative review of behavioural work within the context of conflict adaptation in schizophrenia, focusing on various major conflict adaptation markers: congruency sequence effects, proportion congruency effects, and post-error and post-conflict slowing. The review emphasises both methodological and theoretical aspects that are relevant to the understanding of conflict adaptation in schizophrenia. Based on the currently available set of behavioural studies on conflict adaptation, no clear-cut answer can be provided as to the precise conflict adaptation processes that are impaired (and to what extent) in schizophrenia populations. Future work is needed in state-of-the-art designs in order to reach better insight into the specifics of conflict adaptation impairments associated with schizophrenia.

Type-2 fuzzy logic control based MRAS speed estimator for speed sensorless direct torque and flux control of an induction motor drive.

PubMed

Ramesh, Tejavathu; Kumar Panda, Anup; Shiva Kumar, S

2015-07-01

In this research study, a model reference adaptive system (MRAS) speed estimator for speed sensorless direct torque and flux control (DTFC) of an induction motor drive (IMD) using two adaptation mechanism schemes are proposed to replace the conventional proportional integral controller (PIC). The first adaptation mechanism scheme is based on Type-1 fuzzy logic controller (T1FLC), which is used to achieve high performance sensorless drive in both transient as well as steady state conditions. However, the Type-1 fuzzy sets are certain and unable to work effectively when higher degree of uncertainties presents in the system which can be caused by sudden change in speed or different load disturbances, process noise etc. Therefore, a new Type-2 fuzzy logic controller (T2FLC) based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties and improves the performance and also robust to various load torque and sudden change in speed conditions, respectively. The detailed performances of various adaptation mechanism schemes are carried out in a MATLAB/Simulink environment with a speed sensor and speed sensorless modes of operation when an IMD is operating under different operating conditions, such as, no-load, load and sudden change in speed, respectively. To validate the different control approaches, the system also implemented on real-time system and adequate results are reported for its validation. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.; Ravindran, S. S.

2017-01-01

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Enhancing dissolved oxygen control using an on-line hybrid fuzzy-neural soft-sensing model-based control system in an anaerobic/anoxic/oxic process.

PubMed

Huang, Mingzhi; Wan, Jinquan; Hu, Kang; Ma, Yongwen; Wang, Yan

2013-12-01

An on-line hybrid fuzzy-neural soft-sensing model-based control system was developed to optimize dissolved oxygen concentration in a bench-scale anaerobic/anoxic/oxic (A(2)/O) process. In order to improve the performance of the control system, a self-adapted fuzzy c-means clustering algorithm and adaptive network-based fuzzy inference system (ANFIS) models were employed. The proposed control system permits the on-line implementation of every operating strategy of the experimental system. A set of experiments involving variable hydraulic retention time (HRT), influent pH (pH), dissolved oxygen in the aerobic reactor (DO), and mixed-liquid return ratio (r) was carried out. Using the proposed system, the amount of COD in the effluent stabilized at the set-point and below. The improvement was achieved with optimum dissolved oxygen concentration because the performance of the treatment process was optimized using operating rules implemented in real time. The system allows various expert operational approaches to be deployed with the goal of minimizing organic substances in the outlet while using the minimum amount of energy.

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

PubMed

P, Karuppanan; Mahapatra, Kamala Kanta

2012-01-01

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

Fast Dynamical Coupling Enhances Frequency Adaptation of Oscillators for Robotic Locomotion Control

PubMed Central

Nachstedt, Timo; Tetzlaff, Christian; Manoonpong, Poramate

2017-01-01

Rhythmic neural signals serve as basis of many brain processes, in particular of locomotion control and generation of rhythmic movements. It has been found that specific neural circuits, named central pattern generators (CPGs), are able to autonomously produce such rhythmic activities. In order to tune, shape and coordinate the produced rhythmic activity, CPGs require sensory feedback, i.e., external signals. Nonlinear oscillators are a standard model of CPGs and are used in various robotic applications. A special class of nonlinear oscillators are adaptive frequency oscillators (AFOs). AFOs are able to adapt their frequency toward the frequency of an external periodic signal and to keep this learned frequency once the external signal vanishes. AFOs have been successfully used, for instance, for resonant tuning of robotic locomotion control. However, the choice of parameters for a standard AFO is characterized by a trade-off between the speed of the adaptation and its precision and, additionally, is strongly dependent on the range of frequencies the AFO is confronted with. As a result, AFOs are typically tuned such that they require a comparably long time for their adaptation. To overcome the problem, here, we improve the standard AFO by introducing a novel adaptation mechanism based on dynamical coupling strengths. The dynamical adaptation mechanism enhances both the speed and precision of the frequency adaptation. In contrast to standard AFOs, in this system, the interplay of dynamics on short and long time scales enables fast as well as precise adaptation of the oscillator for a wide range of frequencies. Amongst others, a very natural implementation of this mechanism is in terms of neural networks. The proposed system enables robotic applications which require fast retuning of locomotion control in order to react to environmental changes or conditions. PMID:28377710

Optimization of an organic memristor as an adaptive memory element

NASA Astrophysics Data System (ADS)

Berzina, Tatiana; Smerieri, Anteo; Bernabò, Marco; Pucci, Andrea; Ruggeri, Giacomo; Erokhin, Victor; Fontana, M. P.

2009-06-01

The combination of memory and signal handling characteristics of a memristor makes it a promising candidate for adaptive bioinspired information processing systems. This poses stringent requirements on the basic device, such as stability and reproducibility over a large number of training/learning cycles, and a large anisotropy in the fundamental control material parameter, in our case the electrical conductivity. In this work we report results on the improved performance of electrochemically controlled polymeric memristors, where optimization of a conducting polymer (polyaniline) in the active channel and better environmental control of fabrication methods led to a large increase both in the absolute values of the conductivity in the partially oxydized state of polyaniline and of the on-off conductivity ratio. These improvements are crucial for the application of the organic memristor to adaptive complex signal handling networks.

Surface tension determination using liquid sample micromirror property

NASA Astrophysics Data System (ADS)

Hošek, Jan

2007-05-01

This paper presents an application of adaptive optics principle onto small sample of liquid surface tension measurement. The principle of experimental method devised by Ferguson (1924) is based on measurement of pressure difference across a liquid sample placed into small diameter capillary on condition of one flat meniscus of the liquid sample. Planarity or curvature radius of the capillary tip meniscus has to be measured and controlled, in order to fulfill this condition during measurement. Two different optical set-ups using liquid meniscus micromirror property are presented and its suitability for meniscus profile determination is compared. Meniscus radius optical measurement, data processing and control algorithm of the adaptive micromirror profile set are presented too. The presented adaptive optics system can be used for focal length control of microsystems based on liquid micromirrors or microlenses with long focal distances especially.

Is Cycloxygenase-2 (COX-2) a Major Component of the Mechanism Responsible for Microvascular Remodeling in the Brain?

NASA Astrophysics Data System (ADS)

LaManna, Joseph C.; Sun, Xiaoyan; Ivy, Andre D.; Ward, Nicole L.

We have used a relatively simple model of hypoxia that triggers adaptive structural changes in the cerebral microvasculature to study the process of physiological angiogenesis. This model can be used to obtain mechanistic data for the processes that probably underlie the dynamic structural changes that occur in learning and the control of oxygen availability to the neurovascular unit. These mechanisms are broadly involved in a wide variety of pathophysiological processes. This is the vascular component to CNS functional plasticity, supporting learning and adaptation. The angiogenic process may wane with age, contributing to the decreasing ability to survive metabolic stress and the diminution of neuronal plasticity.

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

USGS Publications Warehouse

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

2015-01-01

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

Adaptive Instrument Module: Space Instrument Controller "Brain" through Programmable Logic Devices

NASA Technical Reports Server (NTRS)

Darrin, Ann Garrison; Conde, Richard; Chern, Bobbie; Luers, Phil; Jurczyk, Steve; Mills, Carl; Day, John H. (Technical Monitor)

2001-01-01

The Adaptive Instrument Module (AIM) will be the first true demonstration of reconfigurable computing with field-programmable gate arrays (FPGAs) in space, enabling the 'brain' of the system to evolve or adapt to changing requirements. In partnership with NASA Goddard Space Flight Center and the Australian Cooperative Research Centre for Satellite Systems (CRC-SS), APL has built the flight version to be flown on the Australian university-class satellite FEDSAT. The AIM provides satellites the flexibility to adapt to changing mission requirements by reconfiguring standardized processing hardware rather than incurring the large costs associated with new builds. This ability to reconfigure the processing in response to changing mission needs leads to true evolveable computing, wherein the instrument 'brain' can learn from new science data in order to perform state-of-the-art data processing. The development of the AIM is significant in its enormous potential to reduce total life-cycle costs for future space exploration missions. The advent of RAM-based FPGAs whose configuration can be changed at any time has enabled the development of the AIM for processing tasks that could not be performed in software. The use of the AIM enables reconfiguration of the FPGA circuitry while the spacecraft is in flight, with many accompanying advantages. The AIM demonstrates the practicalities of using reconfigurable computing hardware devices by conducting a series of designed experiments. These include the demonstration of implementing data compression, data filtering, and communication message processing and inter-experiment data computation. The second generation is the Adaptive Processing Template (ADAPT) which is further described in this paper. The next step forward is to make the hardware itself adaptable and the ADAPT pursues this challenge by developing a reconfigurable module that will be capable of functioning efficiently in various applications. ADAPT will take advantage of radiation tolerant RAM-based field programmable gate array (FPGA) technology to develop a reconfigurable processor that combines the flexibility of a general purpose processor running software with the performance of application specific processing hardware for a variety of high performance computing applications.

Adaptive Memory: Evaluating Alternative Forms of Fitness-Relevant Processing in the Survival Processing Paradigm

PubMed Central

Sandry, Joshua; Trafimow, David; Marks, Michael J.; Rice, Stephen

2013-01-01

Memory may have evolved to preserve information processed in terms of its fitness-relevance. Based on the assumption that the human mind comprises different fitness-relevant adaptive mechanisms contributing to survival and reproductive success, we compared alternative fitness-relevant processing scenarios with survival processing. Participants rated words for relevancy to fitness-relevant and control conditions followed by a delay and surprise recall test (Experiment 1a). Participants recalled more words processed for their relevance to a survival situation. We replicated these findings in an online study (Experiment 2) and a study using revised fitness-relevant scenarios (Experiment 3). Across all experiments, we did not find a mnemonic benefit for alternative fitness-relevant processing scenarios, questioning assumptions associated with an evolutionary account of remembering. Based on these results, fitness-relevance seems to be too wide-ranging of a construct to account for the memory findings associated with survival processing. We propose that memory may be hierarchically sensitive to fitness-relevant processing instructions. We encourage future researchers to investigate the underlying mechanisms responsible for survival processing effects and work toward developing a taxonomy of adaptive memory. PMID:23585858

Context-specific adjustment of cognitive control: Transfer of adaptive control sets.

PubMed

Surrey, Caroline; Dreisbach, Gesine; Fischer, Rico

2017-11-01

Cognitive control protects processing of relevant information from interference by irrelevant information. The level of this processing selectivity can be flexibly adjusted to different control demands (e.g., frequency of conflict) associated with a certain context, leading to the formation of specific context-control associations. In the present study we investigated the robustness and transferability of the acquired context-control demands to new situations. In three experiments, we used a version of the context-specific proportion congruence (CSPC) paradigm, in which each context (e.g., location) is associated with a specific conflict frequency, determining high and low control demands. In a learning phase, associations between context and control demands were established. In a subsequent transfer block, stimulus-response mappings, whole task sets, or context-control demands changed. Results showed an impressive robustness of context-control associations, as context-specific adjustments of control from the learning phase were virtually unaffected by new stimuli and tasks in the transfer block. Only a change of the context-control demand eliminated the context-specific adjustment of control. These findings suggest that context-control associations that have proven to be adaptive in the past are continuously applied despite major changes in the task structure as long as the context-control associations remain the same.

Stimulus relevance modulates contrast adaptation in visual cortex

PubMed Central

Keller, Andreas J; Houlton, Rachael; Kampa, Björn M; Lesica, Nicholas A; Mrsic-Flogel, Thomas D; Keller, Georg B; Helmchen, Fritjof

2017-01-01

A general principle of sensory processing is that neurons adapt to sustained stimuli by reducing their response over time. Most of our knowledge on adaptation in single cells is based on experiments in anesthetized animals. How responses adapt in awake animals, when stimuli may be behaviorally relevant or not, remains unclear. Here we show that contrast adaptation in mouse primary visual cortex depends on the behavioral relevance of the stimulus. Cells that adapted to contrast under anesthesia maintained or even increased their activity in awake naïve mice. When engaged in a visually guided task, contrast adaptation re-occurred for stimuli that were irrelevant for solving the task. However, contrast adaptation was reversed when stimuli acquired behavioral relevance. Regulation of cortical adaptation by task demand may allow dynamic control of sensory-evoked signal flow in the neocortex. DOI: http://dx.doi.org/10.7554/eLife.21589.001 PMID:28130922

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia

PubMed Central

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J. V.; Schulz, Marcel H.; Simon, Martin

2015-01-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. PMID:26231545

Adaptive, fast walking in a biped robot under neuronal control and learning.

PubMed

Manoonpong, Poramate; Geng, Tao; Kulvicius, Tomas; Porr, Bernd; Wörgötter, Florentin

2007-07-01

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori-motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (>3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks.

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.

Self-determination, control, and reactions to changes in workload: a work simulation.

PubMed

Parker, Stacey L; Jimmieson, Nerina L; Amiot, Catherine E

2013-04-01

The objective of this experimental study is to capture the dynamic temporal processes that occur in changing work settings and to test how work control and individuals' motivational predispositions interact to predict reactions to these changes. To this aim, we examine the moderating effects of global self-determined and non-self-determined motivation, at different levels of work control, on participants' adaptation and stress reactivity to changes in workload during four trials of an inbox activity. Workload was increased or decreased at Trial 3, and adaptation to this change was examined via fluctuations in anxiety, coping, motivation, and performance. In support of the hypotheses, results revealed that, for non-self-determined individuals, low work control was stress-buffering and high work control was stress-exacerbating when predicting anxiety and intrinsic motivation. In contrast, for self-determined individuals, high work control facilitated the adaptive use of planning coping in response to a change in workload. Overall, this pattern of results demonstrates that, while high work control was anxiety-provoking and demotivating for non-self-determined individuals, self-determined individuals used high work control to implement an adaptive antecedent-focused emotion regulation strategy (i.e., planning coping) to meet situational demands. Other interactive effects of global motivation emerged on anxiety, active coping, and task performance. These results and their practical implications are discussed.

Spatial Reorientation of Sensorimotor Balance Control in Altered Gravity

NASA Technical Reports Server (NTRS)

Paloski, W. H.; Black, F. L.; Kaufman, G. D.; Reschke, M. F.; Wood, S. J.

2007-01-01

Sensorimotor coordination of body segments following space flight are more pronounced after landing when the head is actively tilted with respect to the trunk. This suggests that central vestibular processing shifts from a gravitational frame of reference to a head frame of reference in microgravity. A major effect of such changes is a significant postural instability documented by standard head-erect Sensory Organization Tests. Decrements in functional performance may still be underestimated when head and gravity reference frames remained aligned. The purpose of this study was to examine adaptive changes in spatial processing for balance control following space flight by incorporating static and dynamic tilts that dissociate head and gravity reference frames. A second aim of this study was to examine the feasibility of altering the re-adaptation process following space flight by providing discordant visual-vestibular-somatosensory stimuli using short-radius pitch centrifugation.

Adaptation to Laterally Displacing Prisms in Anisometropic Amblyopia.

PubMed

Sklar, Jaime C; Goltz, Herbert C; Gane, Luke; Wong, Agnes M F

2015-06-01

Using visual feedback to modify sensorimotor output in response to changes in the external environment is essential for daily function. Prism adaptation is a well-established experimental paradigm to quantify sensorimotor adaptation; that is, how the sensorimotor system adapts to an optically-altered visuospatial environment. Amblyopia is a neurodevelopmental disorder characterized by spatiotemporal deficits in vision that impacts manual and oculomotor function. This study explored the effects of anisometropic amblyopia on prism adaptation. Eight participants with anisometropic amblyopia and 11 visually-normal adults, all right-handed, were tested. Participants pointed to visual targets and were presented with feedback of hand position near the terminus of limb movement in three blocks: baseline, adaptation, and deadaptation. Adaptation was induced by viewing with binocular 11.4° (20 prism diopter [PD]) left-shifting prisms. All tasks were performed during binocular viewing. Participants with anisometropic amblyopia required significantly more trials (i.e., increased time constant) to adapt to prismatic optical displacement than visually-normal controls. During the rapid error correction phase of adaptation, people with anisometropic amblyopia also exhibited greater variance in motor output than visually-normal controls. Amblyopia impacts on the ability to adapt the sensorimotor system to an optically-displaced visual environment. The increased time constant and greater variance in motor output during the rapid error correction phase of adaptation may indicate deficits in processing of visual information as a result of degraded spatiotemporal vision in amblyopia.

Population resequencing reveals candidate genes associated with salinity adaptation of the Pacific oyster Crassostrea gigas.

PubMed

She, Zhicai; Li, Li; Meng, Jie; Jia, Zhen; Que, Huayong; Zhang, Guofan

2018-06-06

The Pacific oyster Crassostrea gigas is an important cultivated shellfish. As a euryhaline species, it has evolved adaptive mechanisms responding to the complex and changeable intertidal environment that it inhabits. To investigate the genetic basis of this salinity adaptation mechanism, we conducted a genome-wide association study using phenotypically differentiated populations (hyposalinity and hypersalinity adaptation populations, and control population), and confirmed our results using an independent population, high-resolution melting, and mRNA expression analysis. For the hyposalinity adaptation, we determined 24 genes, including Cg_CLCN7 (chloride channel protein 7) and Cg_AP1 (apoptosis 1 inhibitor), involved in the ion/water channel and transporter mechanisms, free amino acid and reactive oxygen species metabolism, immune responses, and chemical defence. Three SNPs located on these two genes were significantly differentiated between groups, as was Cg_CLCN7. For the hypersalinity adaptation, the biological process for positive regulating the developmental process was enriched. Enriched gene functions were focused on transcriptional regulation, signal transduction, and cell growth and differentiation, including calmodulin (Cg_CaM) and ficolin-2 (Cg_FCN2). These genes and polymorphisms possibly play an important role in oyster hyposalinity and hypersalinity adaptation. They not only further our understanding of salinity adaptation mechanisms but also provide markers for highly adaptable oyster strains suitable for breeding.

A Model-based B2B (Batch to Batch) Control for An Industrial Batch Polymerization Process

NASA Astrophysics Data System (ADS)

Ogawa, Morimasa

This paper describes overview of a model-based B2B (batch to batch) control for an industrial batch polymerization process. In order to control the reaction temperature precisely, several methods based on the rigorous process dynamics model are employed at all design stage of the B2B control, such as modeling and parameter estimation of the reaction kinetics which is one of the important part of the process dynamics model. The designed B2B control consists of the gain scheduled I-PD/II2-PD control (I-PD with double integral control), the feed-forward compensation at the batch start time, and the model adaptation utilizing the results of the last batch operation. Throughout the actual batch operations, the B2B control provides superior control performance compared with that of conventional control methods.

The ADaptation and Anticipation Model (ADAM) of sensorimotor synchronization

PubMed Central

van der Steen, M. C. (Marieke); Keller, Peter E.

2013-01-01

A constantly changing environment requires precise yet flexible timing of movements. Sensorimotor synchronization (SMS)—the temporal coordination of an action with events in a predictable external rhythm—is a fundamental human skill that contributes to optimal sensory-motor control in daily life. A large body of research related to SMS has focused on adaptive error correction mechanisms that support the synchronization of periodic movements (e.g., finger taps) with events in regular pacing sequences. The results of recent studies additionally highlight the importance of anticipatory mechanisms that support temporal prediction in the context of SMS with sequences that contain tempo changes. To investigate the role of adaptation and anticipatory mechanisms in SMS we introduce ADAM: an ADaptation and Anticipation Model. ADAM combines reactive error correction processes (adaptation) with predictive temporal extrapolation processes (anticipation) inspired by the computational neuroscience concept of internal models. The combination of simulations and experimental manipulations based on ADAM creates a novel and promising approach for exploring adaptation and anticipation in SMS. The current paper describes the conceptual basis and architecture of ADAM. PMID:23772211

Adaptive pattern for autonomous UAV guidance

NASA Astrophysics Data System (ADS)

Sung, Chen-Ko; Segor, Florian

2013-09-01

The research done at the Fraunhofer IOSB in Karlsruhe within the AMFIS project is focusing on a mobile system to support rescue forces in accidents or disasters. The system consists of a ground control station which has the capability to communicate with a large number of heterogeneous sensors and sensor carriers and provides several open interfaces to allow easy integration of additional sensors into the system. Within this research we focus mainly on UAV such as VTOL (Vertical takeoff and Landing) systems because of their ease of use and their high maneuverability. To increase the positioning capability of the UAV, different onboard processing chains of image exploitation for real time detection of patterns on the ground and the interfacing technology for controlling the UAV from the payload during flight were examined. The earlier proposed static ground pattern was extended by an adaptive component which admits an additional visual communication channel to the aircraft. For this purpose different components were conceived to transfer additive information using changeable patterns on the ground. The adaptive ground pattern and their application suitability had to be tested under external influence. Beside the adaptive ground pattern, the onboard process chains and the adaptations to the demands of changing patterns are introduced in this paper. The tracking of the guiding points, the UAV navigation and the conversion of the guiding point positions from the images to real world co-ordinates in video sequences, as well as use limits and the possibilities of an adaptable pattern are examined.

Differences in intersaccadic adaptation transfer between inward and outward adaptation.

PubMed

Schnier, Fabian; Lappe, Markus

2011-09-01

Saccadic adaptation is a mechanism to increase or decrease the amplitude gain of subsequent saccades, if a saccade is not on target. Recent research has shown that the mechanism of gain increasing, or outward adaptation, and the mechanism of gain decreasing, or inward adaptation, rely on partly different processes. We investigate how outward and inward adaptation of reactive saccades transfer to other types of saccades, namely scanning, overlap, memory-guided, and gap saccades. Previous research has shown that inward adaptation of reactive saccades transfers only partially to these other saccade types, suggesting differences in the control mechanisms between these saccade categories. We show that outward adaptation transfers stronger to scanning and overlap saccades than inward adaptation, and that the strength of transfer depends on the duration for which the saccade target is visible before saccade onset. Furthermore, we show that this transfer is mainly driven by an increase in saccade duration, which is apparent for all saccade categories. Inward adaptation, in contrast, is accompanied by a decrease in duration and in peak velocity, but only the peak velocity decrease transfers from reactive saccades to other saccade categories, i.e., saccadic duration remains constant or even increases for test saccades of the other categories. Our results, therefore, show that duration and peak velocity are independent parameters of saccadic adaptation and that they are differently involved in the transfer of adaptation between saccade categories. Furthermore, our results add evidence that inward and outward adaptation are different processes.

Optimal and adaptive methods of processing hydroacoustic signals (review)

NASA Astrophysics Data System (ADS)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

Adaptive quantum computation in changing environments using projective simulation

NASA Astrophysics Data System (ADS)

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-08-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks.

Adaptive quantum computation in changing environments using projective simulation

PubMed Central

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-01-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks. PMID:26260263

Interaction of attentional and motor control processes in handwriting.

PubMed

Brown, T L; Donnenwirth, E E

1990-01-01

The interaction between attentional capacity, motor control processes, and strategic adaptations to changing task demands was investigated in handwriting, a continuous (rather than discrete) skilled performance. Twenty-four subjects completed 12 two-minute handwriting samples under instructions stressing speeded handwriting, normal handwriting, or highly legible handwriting. For half of the writing samples, a concurrent auditory monitoring task was imposed. Subjects copied either familiar (English) or unfamiliar (Latin) passages. Writing speed, legibility ratings, errors in writing and in the secondary auditory task, and a derived measure of the average number of characters held in short-term memory during each sample ("planning unit size") were the dependent variables. The results indicated that the ability to adapt to instructions stressing speed or legibility was substantially constrained by the concurrent listening task and by text familiarity. Interactions between instructions, task concurrence, and text familiarity in the legibility ratings, combined with further analyses of planning unit size, indicated that information throughput from temporary storage mechanisms to motor processes mediated the loss of flexibility effect. Overall, the results suggest that strategic adaptations of a skilled performance to changing task circumstances are sensitive to concurrent attentional demands and that departures from "normal" or "modal" performance require attention.

[Characteristics of night sleep of monkeys on the ground and during space flight on "Kosmos-1667"].

PubMed

Shlyk, G G; Rotenberg, V S; Shirvinskaia, M A; Koro'lkov, V I; Magedov, V S

1989-01-01

The data on the sleep structure of two rhesus monkeys, Vernyi and Gordyi, during their 7-day space flight on Cosmos-1667 and a control study staged a month after recovery are discussed. Sleep structure was changed to the greatest extent the night before launch when additional stress factors were involved. During the first night in space Vernyi showed the so-called recoil effect. Later his sleep structure became stabilized: the specific weight of fast sleep diminished and the fast sleep/delta/sleep index in the first two cycles decreased. In the ground-based control study, sleep parameters pointed to a deteriorated health status of the animal: his fast sleep patterns changed and delta-sleep often reached its maximum after a fast sleep episode. In this animal adaptation was associated with fast sleep restructuring. In the second primate, Gordyi, the process of adaptation was extended and took three nights. This animal consistently showed low parameters of delta-sleep during both fright and postflight control study; it exhibited no recoil phenomenon after its reduction in the prelaunch night. The structure of sleep indicated that it played a lesser role in the overall process of adaptation.

Tomographical process monitoring of laser transmission welding with OCT

NASA Astrophysics Data System (ADS)

Ackermann, Philippe; Schmitt, Robert

2017-06-01

Process control of laser processes still encounters many obstacles. Although these processes are stable, a narrow process parameter window during the process or process deviations have led to an increase on the requirements for the process itself and on monitoring devices. Laser transmission welding as a contactless and locally limited joining technique is well-established in a variety of demanding production areas. For example, sensitive parts demand a particle-free joining technique which does not affect the inner components. Inline integrated non-destructive optical measurement systems capable of providing non-invasive tomographical images of the transparent material, the weld seam and its surrounding areas with micron resolution would improve the overall process. Obtained measurement data enable qualitative feedback into the system to adapt parameters for a more robust process. Within this paper we present the inline monitoring device based on Fourier-domain optical coherence tomography developed within the European-funded research project "Manunet Weldable". This device, after adaptation to the laser transmission welding process is optically and mechanically integrated into the existing laser system. The main target lies within the inline process control destined to extract tomographical geometrical measurement data from the weld seam forming process. Usage of this technology makes offline destructive testing of produced parts obsolete. 1,2,3,4

XML in an Adaptive Framework for Instrument Control

NASA Technical Reports Server (NTRS)

Ames, Troy J.

2004-01-01

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

A calcium-channel homologue required for adaptation to dopamine and serotonin in Caenorhabditis elegans.

PubMed

Schafer, W R; Kenyon, C J

1995-05-04

Processing and storage of information by the nervous system requires the ability to modulate the response of excitable cells to neurotransmitter. A simple process of this type, known as adaptation or desensitization, occurs when prolonged stimulation triggers processes that attenuate the response to neurotransmitter. Here we report that the Caenorhabditis elegans gene unc-2 is required for adaptation to two neurotransmitters, dopamine and serotonin. A loss-of-function mutation in unc-2 resulted in failure to adapt either to paralysis by dopamine or to stimulation of egg laying by serotonin. In addition, unc-2 mutants displayed behaviours similar to those induced by serotonin treatment. We found that unc-2 encodes a homologue of a voltage-sensitive calcium-channel alpha-1 subunit. Expression of unc-2 occurs in two types of neurons implicated in the control of egg laying, a behaviour regulated by serotonin. Unc-2 appears to be required in modulatory neurons to downregulate the response of the egg-laying muscles to serotonin. We propose that adaptation to serotonin occurs through activation of an Unc-2-dependent calcium influx, which modulates the postsynaptic response to serotonin, perhaps by inhibiting the release of a potentiating neuropeptide.

Composite adaptive control of belt polishing force for aero-engine blade

NASA Astrophysics Data System (ADS)

Zhsao, Pengbing; Shi, Yaoyao

2013-09-01

The existing methods for blade polishing mainly focus on robot polishing and manual grinding. Due to the difficulty in high-precision control of the polishing force, the blade surface precision is very low in robot polishing, in particular, quality of the inlet and exhaust edges can not satisfy the processing requirements. Manual grinding has low efficiency, high labor intensity and unstable processing quality, moreover, the polished surface is vulnerable to burn, and the surface precision and integrity are difficult to ensure. In order to further improve the profile accuracy and surface quality, a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed, which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together. By the mode decision-making mechanism, Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value, and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision. Based on the mathematical model of the force-exerting mechanism, simulation analysis is implemented on DSCAC. Simulation results show that the output polishing force can better track the given signal. Finally, the blade polishing experiments are carried out on the designed polishing equipment. Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility, valve dead-time effect, valve nonlinear flow, cylinder friction, measurement noise and other interference on the control precision of polishing force, which has high control precision, strong robustness, strong anti-interference ability and other advantages compared with MRACFNN. The proposed research achieves high-precision control of the polishing force, effectively improves the blade machining precision and surface consistency, and significantly reduces the surface roughness.

Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.

PubMed

Yang, Cheng-Huei; Luo, Ching-Hsing; Yang, Cheng-Hong; Chuang, Li-Yeh

2004-01-01

Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.

Physical constraints on biological integral control design for homeostasis and sensory adaptation.

PubMed

Ang, Jordan; McMillen, David R

2013-01-22

Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Recovery Act: Energy Efficiency of Data Networks through Rate Adaptation (EEDNRA) - Final Technical Report

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

Matthew Andrews; Spyridon Antonakopoulos; Steve Fortune

2011-07-12

This Concept Definition Study focused on developing a scientific understanding of methods to reduce energy consumption in data networks using rate adaptation. Rate adaptation is a collection of techniques that reduce energy consumption when traffic is light, and only require full energy when traffic is at full provisioned capacity. Rate adaptation is a very promising technique for saving energy: modern data networks are typically operated at average rates well below capacity, but network equipment has not yet been designed to incorporate rate adaptation. The Study concerns packet-switching equipment, routers and switches; such equipment forms the backbone of the modern Internet.more » The focus of the study is on algorithms and protocols that can be implemented in software or firmware to exploit hardware power-control mechanisms. Hardware power-control mechanisms are widely used in the computer industry, and are beginning to be available for networking equipment as well. Network equipment has different performance requirements than computer equipment because of the very fast rate of packet arrival; hence novel power-control algorithms are required for networking. This study resulted in five published papers, one internal report, and two patent applications, documented below. The specific technical accomplishments are the following: • A model for the power consumption of switching equipment used in service-provider telecommunication networks as a function of operating state, and measured power-consumption values for typical current equipment. • An algorithm for use in a router that adapts packet processing rate and hence power consumption to traffic load while maintaining performance guarantees on delay and throughput. • An algorithm that performs network-wide traffic routing with the objective of minimizing energy consumption, assuming that routers have less-than-ideal rate adaptivity. • An estimate of the potential energy savings in service-provider networks using feasibly-implementable rate adaptivity. • A buffer-management algorithm that is designed to reduce the size of router buffers, and hence energy consumed. • A packet-scheduling algorithm designed to minimize packet-processing energy requirements. Additional research is recommended in at least two areas: further exploration of rate-adaptation in network switching equipment, including incorporation of rate-adaptation in actual hardware, allowing experimentation in operational networks; and development of control protocols that allow parts of networks to be shut down while minimizing disruption to traffic flow in the network. The research is an integral part of a large effort within Bell Laboratories, Alcatel-Lucent, aimed at dramatic improvements in the energy efficiency of telecommunication networks. This Study did not explicitly consider any commercialization opportunities.« less

Evolutionary transitions in controls reconcile adaptation with continuity of evolution.

PubMed

Badyaev, Alexander V

2018-05-19

Evolution proceeds by accumulating functional solutions, necessarily forming an uninterrupted lineage from past solutions of ancestors to the current design of extant forms. At the population level, this process requires an organismal architecture in which the maintenance of local adaptation does not preclude the ability to innovate in the same traits and their continuous evolution. Representing complex traits as networks enables us to visualize a fundamental principle that resolves tension between adaptation and continuous evolution: phenotypic states encompassing adaptations traverse the continuous multi-layered landscape of past physical, developmental and functional associations among traits. The key concept that captures such traversing is network controllability - the ability to move a network from one state into another while maintaining its functionality (reflecting evolvability) and to efficiently propagate information or products through the network within a phenotypic state (maintaining its robustness). Here I suggest that transitions in network controllability - specifically in the topology of controls - help to explain how robustness and evolvability are balanced during evolution. I will focus on evolutionary transitions in degeneracy of metabolic networks - a ubiquitous property of phenotypic robustness where distinct pathways achieve the same end product - to suggest that associated changes in network controls is a common rule underlying phenomena as distinct as phenotypic plasticity, organismal accommodation of novelties, genetic assimilation, and macroevolutionary diversification. Capitalizing on well understood principles by which network structure translates into function of control nodes, I show that accumulating redundancy in one type of network controls inevitably leads to the emergence of another type of controls, forming evolutionary cycles of network controllability that, ultimately, reconcile local adaptation with continuity of evolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Just-in-time adaptive classifiers-part II: designing the classifier.

PubMed

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

Adaptive pitch control for variable speed wind turbines

DOEpatents

Johnson, Kathryn E [Boulder, CO; Fingersh, Lee Jay [Westminster, CO

2012-05-08

An adaptive method for adjusting blade pitch angle, and controllers implementing such a method, for achieving higher power coefficients. Average power coefficients are determined for first and second periods of operation for the wind turbine. When the average power coefficient for the second time period is larger than for the first, a pitch increment, which may be generated based on the power coefficients, is added (or the sign is retained) to the nominal pitch angle value for the wind turbine. When the average power coefficient for the second time period is less than for the first, the pitch increment is subtracted (or the sign is changed). A control signal is generated based on the adapted pitch angle value and sent to blade pitch actuators that act to change the pitch angle of the wind turbine to the new or modified pitch angle setting, and this process is iteratively performed.

Psychosocial profiles of children with achondroplasia in terms of their short stature-related stress: a nationwide survey in Japan.

PubMed

Nishimura, Naoko; Hanaki, Keiichi

2014-11-01

To assess psychosocial profiles of children with achondroplasia using a nationwide survey. Achondroplasia, showing short stature and disproportionately short limbs, causes physical inconvenience such as difficulty in reaching high objects. It is, however, still controversial whether the condition is associated with psychological problems, especially in childhood. A cross-sectional descriptive design was employed. To evaluate psychosocial profiles and adaptation processes in children with achondroplasia, we developed an inventory of scales based on the psychological stress model of which conceptual framework was comprised of stressor, coping process, coping resource and adaptation outcome domains. Participants were recruited nationwide through the largest advocacy support group for achondroplasia in Japan. Of the 130 group members, 73 X-ray-diagnosed patients, aged 8-18 years, completed the inventory of questionnaires to be analysed. As for the stressor domain, patients experienced short stature-related unpleasant experiences more frequently (z-score: +1·3 in average, +3·9 in physical inconvenience). Nevertheless, these experiences had little effect on the coping process (threat appraisal: -0·2, control appraisal: +0·1) and the adaptation outcome (stress response: +0·3, self-concept: 0·0). Interestingly, self-efficacy in the coping resource domain was noticeably increased (+3·1) and was strongly correlated with most variables in the coping process and in adaptation outcome domains. Although the children with achondroplasia experienced more short stature-related stressors, there was no evidence of any psychosocial maladaptation. This finding suggests that coping process as well as coping resources such as self-efficacy could be important targets for promoting psychological adjustment in children with achondroplasia. To help children with achondroplasia adapt socially, nurses and other healthcare providers should routinely assess their psychological adaptation process, especially cognitive appraisal and self-efficacy.

Adaptive control system having hedge unit and related apparatus and methods

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Salinity Is an Agent of Divergent Selection Driving Local Adaptation of Arabidopsis to Coastal Habitats1[OPEN

PubMed Central

Teres, Joana; Bomblies, Kirsten; Douglas, Alex; Salt, David E.

2015-01-01

Understanding the molecular mechanism of adaptive evolution in plants provides insights into the selective forces driving adaptation and the genetic basis of adaptive traits with agricultural value. The genomic resources available for Arabidopsis (Arabidopsis thaliana) make it well suited to the rapid molecular dissection of adaptive processes. Although numerous potentially adaptive loci have been identified in Arabidopsis, the consequences of divergent selection and migration (both important aspects of the process of local adaptation) for Arabidopsis are not well understood. Here, we use a multiyear field-based reciprocal transplant experiment to detect local populations of Arabidopsis composed of multiple small stands of plants (demes) that are locally adapted to the coast and adjacent inland habitats in northeastern Spain. We identify fitness tradeoffs between plants from these different habitats when grown together in inland and coastal common gardens and also, under controlled conditions in soil excavated from coastal and inland sites. Plants from the coastal habitat also outperform those from inland when grown under high salinity, indicating local adaptation to soil salinity. Sodium can be toxic to plants, and we find its concentration to be elevated in soil and plants sampled at the coast. We conclude that the local adaptation that we observe between adjacent coastal and inland populations is caused by ongoing divergent selection driven by the differential salinity between coastal and inland soils. PMID:26034264

Biological adaptive control model: a mechanical analogue of multi-factorial bone density adaptation.

PubMed

Davidson, Peter L; Milburn, Peter D; Wilson, Barry D

2004-03-21

The mechanism of how bone adapts to every day demands needs to be better understood to gain insight into situations in which the musculoskeletal system is perturbed. This paper offers a novel multi-factorial mathematical model of bone density adaptation which combines previous single-factor models in a single adaptation system as a means of gaining this insight. Unique aspects of the model include provision for interaction between factors and an estimation of the relative contribution of each factor. This interacting system is considered analogous to a Newtonian mechanical system and the governing response equation is derived as a linear version of the adaptation process. The transient solution to sudden environmental change is found to be exponential or oscillatory depending on the balance between cellular activation and deactivation frequencies.

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.

Toward a Generative Model of the Teaching-Learning Process.

ERIC Educational Resources Information Center

McMullen, David W.

Until the rise of cognitive psychology, models of the teaching-learning process (TLP) stressed external rather than internal variables. Models remained general descriptions until control theory introduced explicit system analyses. Cybernetic models emphasize feedback and adaptivity but give little attention to creativity. Research on artificial…

Study of Personnel Attrition and Revocation within U.S. Marine Corps Air Traffic Control Specialties

DTIC Science & Technology

2012-03-01

Entrance Processing Stations (MEPS) and recruit depots, to include non-cognitive testing, such as Navy Computer Adaptive Personality Scales ( NCAPS ...Revocation, Selection, MOS, Regression, Probit, dProbit, STATA, Statistics, Marginal Effects, ASVAB, AFQT, Composite Scores, Screening, NCAPS 15. NUMBER...Navy Computer Adaptive Personality Scales ( NCAPS ), during recruitment. It is also recommended that an economic analysis be conducted comparing the

Modern control concepts in hydrology. [parameter identification in adaptive stochastic control approach

NASA Technical Reports Server (NTRS)

Duong, N.; Winn, C. B.; Johnson, G. R.

1975-01-01

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

The congruency sequence effect 3.0: a critical test of conflict adaptation.

PubMed

Duthoo, Wout; Abrahamse, Elger L; Braem, Senne; Boehler, C Nico; Notebaert, Wim

2014-01-01

Over the last two decades, the congruency sequence effect (CSE) -the finding of a reduced congruency effect following incongruent trials in conflict tasks- has played a central role in advancing research on cognitive control. According to the influential conflict-monitoring account, the CSE reflects adjustments in selective attention that enhance task focus when needed, often termed conflict adaptation. However, this dominant interpretation of the CSE has been called into question by several alternative accounts that stress the role of episodic memory processes: feature binding and (stimulus-response) contingency learning. To evaluate the notion of conflict adaptation in accounting for the CSE, we construed versions of three widely used experimental paradigms (the colour-word Stroop, picture-word Stroop and flanker task) that effectively control for feature binding and contingency learning. Results revealed that a CSE can emerge in all three tasks. This strongly suggests a contribution of attentional control to the CSE and highlights the potential of these unprecedentedly clean paradigms for further examining cognitive control.

The Congruency Sequence Effect 3.0: A Critical Test of Conflict Adaptation

PubMed Central

Duthoo, Wout; Abrahamse, Elger L.; Braem, Senne; Boehler, C. Nico; Notebaert, Wim

2014-01-01

Over the last two decades, the congruency sequence effect (CSE) –the finding of a reduced congruency effect following incongruent trials in conflict tasks– has played a central role in advancing research on cognitive control. According to the influential conflict-monitoring account, the CSE reflects adjustments in selective attention that enhance task focus when needed, often termed conflict adaptation. However, this dominant interpretation of the CSE has been called into question by several alternative accounts that stress the role of episodic memory processes: feature binding and (stimulus-response) contingency learning. To evaluate the notion of conflict adaptation in accounting for the CSE, we construed versions of three widely used experimental paradigms (the colour-word Stroop, picture-word Stroop and flanker task) that effectively control for feature binding and contingency learning. Results revealed that a CSE can emerge in all three tasks. This strongly suggests a contribution of attentional control to the CSE and highlights the potential of these unprecedentedly clean paradigms for further examining cognitive control. PMID:25340396

The effects of adaptive working memory training and mindfulness meditation training on processing efficiency and worry in high worriers.

PubMed

Course-Choi, Jenna; Saville, Harry; Derakshan, Nazanin

2017-02-01

Worry is the principle characteristic of generalised anxiety disorder, and has been linked to deficient attentional control, a main function of working memory (WM). Adaptive WM training and mindfulness meditation practice (MMP) have both shown potential to increase attentional control. The present study hence investigates the individual and combined effects of MMP and a dual adaptive n-back task on a non-clinical, randomised sample of high worriers. 60 participants were tested before and after seven days of training. Assessment included self-report questionnaires, as well as performance tasks measuring attentional control and working memory capacity. Combined training resulted in continued reduction in worry in the week after training, highlighting the potential of utilising n-back training as an adjunct to established clinical treatment. Engagement with WM training correlated with immediate improvements in attentional control and resilience, with worry decreasing over time. Implications of these findings and suggestions for future research are discussed. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Explicit control of adaptive automation under different levels of environmental stress.

PubMed

Sauer, Jürgen; Kao, Chung-Shan; Wastell, David; Nickel, Peter

2011-08-01

This article examines the effectiveness of three different forms of explicit control of adaptive automation under low- and high-stress conditions, operationalised by different levels of noise. In total, 60 participants were assigned to one of three types of automation design (free, prompted and forced choice). They were trained for 4 h on a highly automated simulation of a process control environment, called AutoCAMS. This was followed by a 4-h testing session under noise exposure and quiet conditions. Measures of performance, psychophysiology and subjective reactions were taken. The results showed that all three modes of explicit control of adaptive automation modes were able to attenuate the negative effects of noise. This was partly due to the fact that operators opted for higher levels of automation under noise. It also emerged that forced choice showed marginal advantages over the two other automation modes. Statement of Relevance: This work is relevant to the design of adaptive automation since it emphasises the need to consider the impact of work-related stressors during task completion. During the presence of stressors, different forms of operator support through automation may be required than under more favourable working conditions.

Sleep deprivation selectively disrupts top-down adaptation to cognitive conflict in the Stroop test.

PubMed

Gevers, Wim; Deliens, Gaetane; Hoffmann, Sophie; Notebaert, Wim; Peigneux, Philippe

2015-12-01

Sleep deprivation is known to exert detrimental effects on various cognitive domains, including attention, vigilance and working memory. Seemingly at odds with these findings, prior studies repeatedly failed to evidence an impact of prior sleep deprivation on cognitive interference in the Stroop test, a hallmark paradigm in the study of cognitive control abilities. The present study investigated further the effect of sleep deprivation on cognitive control using an adapted version of the Stroop test that allows to segregate top-down (attentional reconfiguration on incongruent items) and bottom-up (facilitated processing after repetitions in responses and/or features of stimuli) components of performance. Participants underwent a regular night of sleep or a night of total sleep deprivation before cognitive testing. Results disclosed that sleep deprivation selectively impairs top-down adaptation mechanisms: cognitive control no longer increased upon detection of response conflict at the preceding trial. In parallel, bottom-up abilities were found unaffected by sleep deprivation: beneficial effects of stimulus and response repetitions persisted. Changes in vigilance states due to sleep deprivation selectively impact on cognitive control in the Stroop test by affecting top-down, but not bottom-up, mechanisms that guide adaptive behaviours. © 2015 European Sleep Research Society.

An infrared modular panoramic imaging objective

NASA Astrophysics Data System (ADS)

Palmer, Troy A.; Alexay, Christopher C.

2004-08-01

We describe the optical and mechanical design of an athermal infrared objective lens with an afocal anamorphic adapter. The lens presented consists of two modules: an athermal 25mm F/2.3 mid-wave IR objective lens and an optional panoramic adapter. The adapter utilizes anamorphic lenses to create unique image control. The result of which enables an independent horizontal wide field of view, while preserving the original narrow vertical field. We have designed, fabricated and tested two such lenses. A summary of the assembly and testing process is also presented.

Adaptive hyperspectral imager: design, modeling, and control

NASA Astrophysics Data System (ADS)

McGregor, Scot; Lacroix, Simon; Monmayrant, Antoine

2015-08-01

An adaptive, hyperspectral imager is presented. We propose a system with easily adaptable spectral resolution, adjustable acquisition time, and high spatial resolution which is independent of spectral resolution. The system yields the possibility to define a variety of acquisition schemes, and in particular near snapshot acquisitions that may be used to measure the spectral content of given or automatically detected regions of interest. The proposed system is modelled and simulated, and tests on a first prototype validate the approach to achieve near snapshot spectral acquisitions without resorting to any computationally heavy post-processing, nor cumbersome calibration

Adaptive Controller Effects on Pilot Behavior

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Self-organizing high-order cognitive functions in artificial agents: implications for possible prefrontal cortex mechanisms.

PubMed

Maniadakis, Michail; Trahanias, Panos; Tani, Jun

2012-09-01

In our daily life, we often adapt plans and behaviors according to dynamically changing world circumstances, selecting activities that make us feel more confident about the future. In this adaptation, the prefrontal cortex (PFC) is believed to have an important role, applying executive control on other cognitive processes to achieve context switching and confidence monitoring; however, many questions remain open regarding the nature of neural processes supporting executive control. The current work explores possible mechanisms of this high-order cognitive function, transferring executing control in the domain of artificial cognitive systems. In particular, we study the self-organization of artificial neural networks accomplishing a robotic rule-switching task analogous to the Wisconsin Card Sorting Test. The obtained results show that behavioral rules may be encoded in neuro-dynamic attractors, with their geometric arrangements in phase space affecting the shaping of confidence. Analysis of the emergent dynamical structures suggests possible explanations of the interactions of high-level and low-level processes in the real brain. Copyright © 2012 Elsevier Ltd. All rights reserved.

Chemometrics-based process analytical technology (PAT) tools: applications and adaptation in pharmaceutical and biopharmaceutical industries.

PubMed

Challa, Shruthi; Potumarthi, Ravichandra

2013-01-01

Process analytical technology (PAT) is used to monitor and control critical process parameters in raw materials and in-process products to maintain the critical quality attributes and build quality into the product. Process analytical technology can be successfully implemented in pharmaceutical and biopharmaceutical industries not only to impart quality into the products but also to prevent out-of-specifications and improve the productivity. PAT implementation eliminates the drawbacks of traditional methods which involves excessive sampling and facilitates rapid testing through direct sampling without any destruction of sample. However, to successfully adapt PAT tools into pharmaceutical and biopharmaceutical environment, thorough understanding of the process is needed along with mathematical and statistical tools to analyze large multidimensional spectral data generated by PAT tools. Chemometrics is a chemical discipline which incorporates both statistical and mathematical methods to obtain and analyze relevant information from PAT spectral tools. Applications of commonly used PAT tools in combination with appropriate chemometric method along with their advantages and working principle are discussed. Finally, systematic application of PAT tools in biopharmaceutical environment to control critical process parameters for achieving product quality is diagrammatically represented.

Modeling, simulation and control for a cryogenic fluid management facility, preliminary report

NASA Technical Reports Server (NTRS)

Turner, Max A.; Vanbuskirk, P. D.

1986-01-01

The synthesis of a control system for a cryogenic fluid management facility was studied. The severe demand for reliability as well as instrumentation and control unique to the Space Station environment are prime considerations. Realizing that the effective control system depends heavily on quantitative description of the facility dynamics, a methodology for process identification and parameter estimation is postulated. A block diagram of the associated control system is also produced. Finally, an on-line adaptive control strategy is developed utilizing optimization of the velocity form control parameters (proportional gains, integration and derivative time constants) in appropriate difference equations for direct digital control. Of special concern are the communications, software and hardware supporting interaction between the ground and orbital systems. It is visualized that specialist in the OSI/ISO utilizing the Ada programming language will influence further development, testing and validation of the simplistic models presented here for adaptation to the actual flight environment.

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation.

PubMed

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2013-09-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro .

A Power-Efficient Wireless System With Adaptive Supply Control for Deep Brain Stimulation

PubMed Central

Lee, Hyung-Min; Park, Hangue; Ghovanloo, Maysam

2014-01-01

A power-efficient wireless stimulating system for a head-mounted deep brain stimulator (DBS) is presented. A new adaptive rectifier generates a variable DC supply voltage from a constant AC power carrier utilizing phase control feedback, while achieving high AC-DC power conversion efficiency (PCE) through active synchronous switching. A current-controlled stimulator adopts closed-loop supply control to automatically adjust the stimulation compliance voltage by detecting stimulation site potentials through a voltage readout channel, and improve the stimulation efficiency. The stimulator also utilizes closed-loop active charge balancing to maintain the residual charge at each site within a safe limit, while receiving the stimulation parameters wirelessly from the amplitude-shift-keyed power carrier. A 4-ch wireless stimulating system prototype was fabricated in a 0.5-μm 3M2P standard CMOS process, occupying 2.25 mm². With 5 V peak AC input at 2 MHz, the adaptive rectifier provides an adjustable DC output between 2.5 V and 4.6 V at 2.8 mA loading, resulting in measured PCE of 72 ~ 87%. The adaptive supply control increases the stimulation efficiency up to 30% higher than a fixed supply voltage to 58 ~ 68%. The prototype wireless stimulating system was verified in vitro. PMID:24678126

Process Analytical Technology (PAT): batch-to-batch reproducibility of fermentation processes by robust process operational design and control.

PubMed

Gnoth, S; Jenzsch, M; Simutis, R; Lübbert, A

2007-10-31

The Process Analytical Technology (PAT) initiative of the FDA is a reaction on the increasing discrepancy between current possibilities in process supervision and control of pharmaceutical production processes and its current application in industrial manufacturing processes. With rigid approval practices based on standard operational procedures, adaptations of production reactors towards the state of the art were more or less inhibited for long years. Now PAT paves the way for continuous process and product improvements through improved process supervision based on knowledge-based data analysis, "Quality-by-Design"-concepts, and, finally, through feedback control. Examples of up-to-date implementations of this concept are presented. They are taken from one key group of processes in recombinant pharmaceutical protein manufacturing, the cultivations of genetically modified Escherichia coli bacteria.

Study of adaptation to altered gravity through systems analysis of motor control.

PubMed

Fox, R A; Daunton, N G; Corcoran, M L

1998-01-01

Maintenance of posture and production of functional, coordinated movement demand integration of sensory feedback with spinal and supra-spinal circuitry to produce adaptive motor control in altered gravity (G). To investigate neuroplastic processes leading to optimal performance in altered G we have studied motor control in adult rats using a battery of motor function tests following chronic exposure to various treatments (hyper-G, hindlimb suspension, chemical distruction of hair cells, space flight). These treatments differentially affect muscle fibers, vestibular receptors, and behavioral compensations and, in consequence, differentially disrupt air righting, swimming, posture and gait. The time-course of recovery from these disruptions varies depending on the function tested and the duration and type of treatment. These studies, with others (e.g., D'Amelio et al. in this volume), indicate that adaptation to altered gravity involves alterations in multiple sensory-motor systems that change at different rates. We propose that the use of parallel studies under different altered G conditions will most efficiently lead to an understanding of the modifications in central (neural) and peripheral (sensory and neuromuscular) systems that underlie sensory-motor adaptation in active, intact individuals.

Study of adaptation to altered gravity through systems analysis of motor control

NASA Astrophysics Data System (ADS)

Fox, R. A.; Daunton, N. G.; Corcoran, M. L.

Maintenance of posture and production of functional, coordinated movement demand integration of sensory feedback with spinal and supra-spinal circuitry to produce adaptive motor control in altered gravity (G). To investigate neuroplastic processes leading to optimal performance in altered G we have studied motor control in adult rats using a battery of motor function tests following chronic exposure to various treatments (hyper-G, hindlimb suspension, chemical distruction of hair cells, space flight). These treatments differentially affect muscle fibers, vestibular receptors, and behavioral compensations and, in consequence, differentially disrupt air righting, swimming, posture and gait. The time-course of recovery from these disruptions varies depending on the function tested and the duration and type of treatment. These studies, with others (e.g., D'Amelio et al. in this volume), indicate that adaptation to altered gravity involves alterations in multiple sensory-motor systems that change at different rates. We propose that the use of parallel studies under different altered G conditions will most efficiently lead to an understanding of the modifications in central (neural) and peripheral (sensory and neuromuscular) systems that underlie sensory-motor adaptation in active, intact individuals.

Cognitive Control Acts Locally

ERIC Educational Resources Information Center

Notebaert, Wim; Verguts, Tom

2008-01-01

Cognitive control adjusts information processing to momentary needs and task requirements. We investigated conflict adaptation when participants are performing two tasks, a Simon task and a SNARC task. The results indicated that one congruency effect (e.g., Simon) was reduced after conflict in the other task (e.g., SNARC), but only when both tasks…

Multiple input electrode gap controller

DOEpatents

Hysinger, C.L.; Beaman, J.J.; Melgaard, D.K.; Williamson, R.L.

1999-07-27

A method and apparatus for controlling vacuum arc remelting (VAR) furnaces by estimation of electrode gap based on a plurality of secondary estimates derived from furnace outputs. The estimation is preferably performed by Kalman filter. Adaptive gain techniques may be employed, as well as detection of process anomalies such as glows. 17 figs.

Multiple input electrode gap controller

DOEpatents

Hysinger, Christopher L.; Beaman, Joseph J.; Melgaard, David K.; Williamson, Rodney L.

1999-01-01

A method and apparatus for controlling vacuum arc remelting (VAR) furnaces by estimation of electrode gap based on a plurality of secondary estimates derived from furnace outputs. The estimation is preferably performed by Kalman filter. Adaptive gain techniques may be employed, as well as detection of process anomalies such as glows.

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

NASA Technical Reports Server (NTRS)

Barg, J.

1982-01-01

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

Mechanisms underlying flexible adaptation of cognitive control: behavioral and neuroimaging evidence in a flanker task.

PubMed

Zurawska Vel Grajewska, Blandyna; Sim, Eun-Jin; Hoenig, Klaus; Herrnberger, Bärbel; Kiefer, Markus

2011-11-03

Cognitive control can be adapted flexibly according to the conflict level in a given situation. In the Eriksen flanker task, interference evoked by flankers is larger in conditions with a higher, rather than a lower proportion of compatible trials. Such compatibility ratio effects also occur for stimuli presented at two spatial locations suggesting that different cognitive control settings can be simultaneously maintained. However, the conditions and the neural correlates of this flexible adaptation of cognitive control are only poorly understood. In the present study, we further elucidated the mechanisms underlying the simultaneous maintenance of two cognitive control settings. In behavioral experiments, stimuli were presented centrally above and below fixation and hence processed by both hemispheres or lateralized to stimulate hemispheres differentially. The different compatibility ratio at two stimulus locations had a differential influence on the flanker effect in both experiments. In an fMRI experiment, blocks with an identical compatibility ratio at two central spatial locations elicited stronger activity in a network of prefrontal and parietal brain areas, which are known to be involved in conflict resolution and cognitive control, as compared with blocks with a different compatibility ratio at the same spatial locations. This demonstrates that the simultaneous maintenance of two conflicting control settings vs. one single setting does not recruit additional neural circuits suggesting the involvement of one single cognitive control system. Instead a crosstalk between multiple control settings renders adaptation of cognitive control more efficient when only one uniform rather than two different control settings has to be simultaneously maintained. Copyright © 2011 Elsevier B.V. All rights reserved.

The use of information theory in evolutionary biology.

PubMed

Adami, Christoph

2012-05-01

Information is a key concept in evolutionary biology. Information stored in a biological organism's genome is used to generate the organism and to maintain and control it. Information is also that which evolves. When a population adapts to a local environment, information about this environment is fixed in a representative genome. However, when an environment changes, information can be lost. At the same time, information is processed by animal brains to survive in complex environments, and the capacity for information processing also evolves. Here, I review applications of information theory to the evolution of proteins and to the evolution of information processing in simulated agents that adapt to perform a complex task. © 2012 New York Academy of Sciences.

Reaction pathways in atomistic models of thin film growth

NASA Astrophysics Data System (ADS)

Lloyd, Adam L.; Zhou, Ying; Yu, Miao; Scott, Chris; Smith, Roger; Kenny, Steven D.

2017-10-01

The atomistic processes that form the basis of thin film growth often involve complex multi-atom movements of atoms or groups of atoms on or close to the surface of a substrate. These transitions and their pathways are often difficult to predict in advance. By using an adaptive kinetic Monte Carlo (AKMC) approach, many complex mechanisms can be identified so that the growth processes can be understood and ultimately controlled. Here the AKMC technique is briefly described along with some special adaptions that can speed up the simulations when, for example, the transition barriers are small. Examples are given of such complex processes that occur in different material systems especially for the growth of metals and metallic oxides.

Effects of Selected Task Performance Criteria at Initiating Adaptive Task Real locations

NASA Technical Reports Server (NTRS)

Montgomery, Demaris A.

2001-01-01

In the current report various performance assessment methods used to initiate mode transfers between manual control and automation for adaptive task reallocation were tested. Participants monitored two secondary tasks for critical events while actively controlling a process in a fictional system. One of the secondary monitoring tasks could be automated whenever operators' performance was below acceptable levels. Automation of the secondary task and transfer of the secondary task back to manual control were either human- or machine-initiated. Human-initiated transfers were based on the operator's assessment of the current task demands while machine-initiated transfers were based on the operators' performance. Different performance assessment methods were tested in two separate experiments.

Artificial blood circulation: stabilization, physiological control, and optimization.

PubMed

Lerner, A Y

1990-04-01

The requirements for creating an efficient Artificial Blood Circulation System (ABCS) have been determined. A hierarchical three-level adaptive control system is suggested for ABCS to solve the following problems: stabilization of the circulation conditions, left and right pump coordination, physiological control for maintaining a proper relation between the cardiac output and the level of gas exchange required for metabolism, and optimization of the system behavior. The adaptations to varying load and body parameters will be accomplished using the signals which characterize the real-time computer-processed values of correlations between the changes in hydraulic resistance of blood vessels, or the changes in aortic pressure, and the oxygen (or carbon dioxide) concentration.

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.

Development of cognitive and affective control networks and decision making.

PubMed

Kar, Bhoomika R; Vijay, Nivita; Mishra, Shreyasi

2013-01-01

Cognitive control and decision making are two important research areas in the realm of higher-order cognition. Control processes such as interference control and monitoring in cognitive and affective contexts have been found to influence the process of decision making. Development of control processes follows a gradual growth pattern associated with the prolonged maturation of underlying neural circuits including the lateral prefrontal cortex, anterior cingulate, and the medial prefrontal cortex. These circuits are also involved in the control of processes that influences decision making, particularly with respect to choice behavior. Developmental studies on affective control have shown distinct patterns of brain activity with adolescents showing greater activation of amygdala whereas adults showing greater activity in ventral prefrontal cortex. Conflict detection, monitoring, and adaptation involve anticipation and subsequent performance adjustments which are also critical to complex decision making. We discuss the gradual developmental patterns observed in two of our studies on conflict monitoring and adaptation in affective and nonaffective contexts. Findings of these studies indicate the need to look at the differences in the effects of the development of cognitive and affective control on decision making in children and particularly adolescents. Neuroimaging studies have shown the involvement of separable neural networks for cognitive (medial prefrontal cortex and anterior cingulate) and affective control (amygdala, ventral medial prefrontal cortex) shows that one system can affect the other also at the neural level. Hence, an understanding of the interaction and balance between the cognitive and affective brain networks may be crucial for self-regulation and decision making during the developmental period, particularly late childhood and adolescence. The chapter highlights the need for empirical investigation on the interaction between the different aspects of cognitive control and decision making from a developmental perspective. Copyright © 2013 Elsevier B.V. All rights reserved.

Sustaining a Mature Risk Management Process: Ensuring the International Space Station for a Vibrant Future

NASA Technical Reports Server (NTRS)

Raftery, Michael; Carter-Journet, Katrina

2013-01-01

The International Space Station (ISS) risk management methodology is an example of a mature and sustainable process. Risk management is a systematic approach used to proactively identify, analyze, plan, track, control, communicate, and document risks to help management make risk-informed decisions that increase the likelihood of achieving program objectives. The ISS has been operating in space for over 14 years and permanently crewed for over 12 years. It is the longest surviving habitable vehicle in low Earth orbit history. Without a mature and proven risk management plan, it would be increasingly difficult to achieve mission success throughout the life of the ISS Program. A successful risk management process must be able to adapt to a dynamic program. As ISS program-level decision processes have evolved, so too has the ISS risk management process continued to innovate, improve, and adapt. Constant adaptation of risk management tools and an ever-improving process is essential to the continued success of the ISS Program. Above all, sustained support from program management is vital to risk management continued effectiveness. Risk management is valued and stressed as an important process by the ISS Program.

Robust adaptive sliding mode control for uncertain systems with unknown time-varying delay input.

PubMed

Benamor, Anouar; Messaoud, Hassani

2018-05-02

This article focuses on robust adaptive sliding mode control law for uncertain discrete systems with unknown time-varying delay input, where the uncertainty is assumed unknown. The main results of this paper are divided into three phases. In the first phase, we propose a new sliding surface is derived within the Linear Matrix Inequalities (LMIs). In the second phase, using the new sliding surface, the novel Robust Sliding Mode Control (RSMC) is proposed where the upper bound of uncertainty is supposed known. Finally, the novel approach of Robust Adaptive Sliding ModeControl (RASMC) has been defined for this type of systems, where the upper limit of uncertainty which is assumed unknown. In this new approach, we have estimate the upper limit of uncertainties and we have determined the control law based on a sliding surface that will converge to zero. This novel control laws are been validated in simulation on an uncertain numerical system with good results and comparative study. This efficiency is emphasized through the application of the new controls on the two physical systems which are the process trainer PT326 and hydraulic system two tanks. Published by Elsevier Ltd.

Getting Your Sea Legs.

PubMed

Stoffregen, Thomas A; Chen, Fu-Chen; Varlet, Manuel; Alcantara, Cristina; Bardy, Benoît G

2013-01-01

Sea travel mandates changes in the control of the body. The process by which we adapt bodily control to life at sea is known as getting one's sea legs. We conducted the first experimental study of bodily control as maritime novices adapted to motion of a ship at sea. We evaluated postural activity (stance width, stance angle, and the kinematics of body sway) before and during a sea voyage. In addition, we evaluated the role of the visible horizon in the control of body sway. Finally, we related data on postural activity to two subjective experiences that are associated with sea travel; seasickness, and mal de debarquement. Our results revealed rapid changes in postural activity among novices at sea. Before the beginning of the voyage, the temporal dynamics of body sway differed among participants as a function of their (subsequent) severity of seasickness. Body sway measured at sea differed among participants as a function of their (subsequent) experience of mal de debarquement. We discuss implications of these results for general theories of the perception and control of bodily orientation, for the etiology of motion sickness, and for general phenomena of perceptual-motor adaptation and learning.

Depth Cue Integration in an Active Control Paradigm

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Sweet, Barabara T.; Shafto, Meredith; Null, Cynthia H. (Technical Monitor)

1995-01-01

Numerous models of depth cue integration have been proposed. Of particular interest is how the visual system processes discrepent cues, as might arise when viewing synthetic displays. A powerful paradigm for examining this integration process can be adapted from manual control research. This methodology introduces independent disturbances in the candidate cues, then performs spectral analysis of subjects' resulting motoric responses (e.g., depth matching). We will describe this technique and present initial findings.

Fault tolerant control of multivariable processes using auto-tuning PID controller.

PubMed

Yu, Ding-Li; Chang, T K; Yu, Ding-Wen

2005-02-01

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia.

PubMed

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J V; Schulz, Marcel H; Simon, Martin

2015-08-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Training working memory to improve attentional control in anxiety: A proof-of-principle study using behavioral and electrophysiological measures.

PubMed

Sari, Berna A; Koster, Ernst H W; Pourtois, Gilles; Derakshan, Nazanin

2016-12-01

Trait anxiety is associated with impairments in attentional control and processing efficiency (see Berggren & Derakshan, 2013, for a review). Working memory training using the adaptive dual n-back task has shown to improve attentional control in subclinical depression with transfer effects at the behavioral and neural level on a working memory task (Owens, Koster, & Derakshan, 2013). Here, we examined the beneficial effects of working memory training on attentional control in pre-selected high trait anxious individuals who underwent a three week daily training intervention using the adaptive dual n-back task. Pre and post outcome measures of attentional control were assessed using a Flanker task that included a stress induction and an emotional a Antisaccade task (with angry and neutral faces as target). Resting state EEG (theta/beta ratio) was recorded to as a neural marker of trait attentional control. Our results showed that adaptive working memory training improved attentional control with transfer effects on the Flanker task and resting state EEG, but effects of training on the Antisaccade task were less conclusive. Finally, training related gains were associated with lower levels of trait anxiety at post (vs pre) intervention. Our results demonstrate that adaptive working memory training in anxiety can have beneficial effects on attentional control and cognitive performance that may protect against emotional vulnerability in individuals at risk of developing clinical anxiety. Copyright © 2015 Elsevier B.V. All rights reserved.

A novel patterning control strategy based on real-time fingerprint recognition and adaptive wafer level scanner optimization

NASA Astrophysics Data System (ADS)

Cekli, Hakki Ergun; Nije, Jelle; Ypma, Alexander; Bastani, Vahid; Sonntag, Dag; Niesing, Henk; Zhang, Linmiao; Ullah, Zakir; Subramony, Venky; Somasundaram, Ravin; Susanto, William; Matsunobu, Masazumi; Johnson, Jeff; Tabery, Cyrus; Lin, Chenxi; Zou, Yi

2018-03-01

In addition to lithography process and equipment induced variations, processes like etching, annealing, film deposition and planarization exhibit variations, each having their own intrinsic characteristics and leaving an effect, a `fingerprint', on the wafers. With ever tighter requirements for CD and overlay, controlling these process induced variations is both increasingly important and increasingly challenging in advanced integrated circuit (IC) manufacturing. For example, the on-product overlay (OPO) requirement for future nodes is approaching <3nm, requiring the allowable budget for process induced variance to become extremely small. Process variance control is seen as an bottleneck to further shrink which drives the need for more sophisticated process control strategies. In this context we developed a novel `computational process control strategy' which provides the capability of proactive control of each individual wafer with aim to maximize the yield, without introducing a significant impact on metrology requirements, cycle time or productivity. The complexity of the wafer process is approached by characterizing the full wafer stack building a fingerprint library containing key patterning performance parameters like Overlay, Focus, etc. Historical wafer metrology is decomposed into dominant fingerprints using Principal Component Analysis. By associating observed fingerprints with their origin e.g. process steps, tools and variables, we can give an inline assessment of the strength and origin of the fingerprints on every wafer. Once the fingerprint library is established, a wafer specific fingerprint correction recipes can be determined based on its processing history. Data science techniques are used in real-time to ensure that the library is adaptive. To realize this concept, ASML TWINSCAN scanners play a vital role with their on-board full wafer detection and exposure correction capabilities. High density metrology data is created by the scanner for each wafer and on every layer during the lithography steps. This metrology data will be used to obtain the process fingerprints. Also, the per exposure and per wafer correction potential of the scanners will be utilized for improved patterning control. Additionally, the fingerprint library will provide early detection of excursions for inline root cause analysis and process optimization guidance.

Performing Verification and Validation in Reuse-Based Software Engineering

NASA Technical Reports Server (NTRS)

Addy, Edward A.

1999-01-01

The implementation of reuse-based software engineering not only introduces new activities to the software development process, such as domain analysis and domain modeling, it also impacts other aspects of software engineering. Other areas of software engineering that are affected include Configuration Management, Testing, Quality Control, and Verification and Validation (V&V). Activities in each of these areas must be adapted to address the entire domain or product line rather than a specific application system. This paper discusses changes and enhancements to the V&V process, in order to adapt V&V to reuse-based software engineering.

An experimental adaptive array to suppress weak interfering signals

NASA Technical Reports Server (NTRS)

Walton, Eric K.; Gupta, Inder J.; Ksienski, Aharon A.; Ward, James

1988-01-01

An experimental adaptive antenna system to suppress weak interfering signals is described. It is a sidelobe canceller with two auxiliary elements. Modified feedback loops are used to control the array weights. The received signals are simulated in hardware for parameter control. Digital processing is used for algorithm implementation and performance evaluation. The experimental results are presented. They show that interfering signals as much as 10 dB below the thermal noise level in the main channel are suppressed by 20-30 dB. Such a system has potential application in suppressing the interference encountered in direct broadcast satellite communication systems.

Independent sailing with high tetraplegia using sip and puff controls: integration into a community sailing center.

PubMed

Rojhani, Solomon; Stiens, Steven A; Recio, Albert C

2017-07-01

We are continually rediscovering how adapted recreational activity complements the rehabilitation process, enriches patients' lives and positively impacts outcome measures. Although sports for people with spinal cord injuries (SCI) has achieved spectacular visibility, participation by high cervical injuries is often restricted due to poor accessibility, safety concerns, lack of adaptability, and high costs of technology. We endeavor to demonstrate the mechanisms, adaptability, accessibility, and benefits the sport of sailing creates in the rehabilitative process. Our sailor is a 27-year-old man with a history of traumatic SCI resulting in C4 complete tetraplegia. The participant completed an adapted introductory sailing course, and instruction on the sip-and-puff sail and tiller control mechanism. With practice, he navigated an on-water course in moderate winds of 5 to 15 knots. Despite trends toward shorter rehabilitation stays, aggressive transdisciplinary collaboration with recreation therapy can provide community and natural environment experiences while inpatient and continuing post discharge. Such peak physical and psychological experiences provide a positive perspective for the future that can be shared on the inpatient unit, with families and support systems like sailing clubs in the community. Rehabilitation theory directs a team process to achieve patient self-awareness and initiate self-actualization in spite of disablement. Utilization of local community sailing centers that have provided accessible assisted options provides person-centered self-realization of goals as assisted by family and natural supports. Such successful patients become native guides for others seeking the same experience.

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

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

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

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

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

The combined effects of action observation and passive proprioceptive training on adaptive motor learning.

PubMed

Lei, Yuming; Bao, Shancheng; Wang, Jinsung

2016-09-07

Sensorimotor adaptation can be induced by action observation, and also by passive training. Here, we investigated the effect of a protocol that combined action observation and passive training on visuomotor adaptation, by comparing it with the effect of action observation or passive training alone. Subjects were divided into five conditions during the training session: (1) action observation, in which the subjects watched a video of a model who adapted to a novel visuomotor rotation; (2) proprioceptive training, in which the subject's arm was moved passively to target locations that were associated with desired trajectories; (3) combined training, in which the subjects watched the video of a model during a half of the session and experienced passive movements during the other half; (4) active training, in which the subjects adapted actively to the rotation; and (5) a control condition, in which the subjects did not perform any task. Following that session, all subjects adapted to the same visuomotor rotation. Results showed that the subjects in the combined training condition adapted to the rotation significantly better than those in the observation or proprioceptive training condition, although their performance was not as good as that of those who adapted actively. These findings suggest that although a protocol that combines action observation and passive training consists of all the processes involved in active training (error detection and correction, effector-specific and proprioceptively based reaching movements), these processes in that protocol may work differently as compared to a protocol in which the same processes are engaged actively. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Decentralized Adaptive Control For Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

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

Study of the modifications needed for efficient operation of NASTRAN on the Control Data Corporation STAR-100 computer

NASA Technical Reports Server (NTRS)

1975-01-01

NASA structural analysis (NASTRAN) computer program is operational on three series of third generation computers. The problem and difficulties involved in adapting NASTRAN to a fourth generation computer, namely, the Control Data STAR-100, are discussed. The salient features which distinguish Control Data STAR-100 from third generation computers are hardware vector processing capability and virtual memory. A feasible method is presented for transferring NASTRAN to Control Data STAR-100 system while retaining much of the machine-independent code. Basic matrix operations are noted for optimization for vector processing.

Adaptive piezoelectric sensoriactuators for active structural acoustic control

NASA Astrophysics Data System (ADS)

Vipperman, Jeffrey Stuart

1997-09-01

A new transducer technology with application to active control systems, modal analysis, and autonomous system health monitoring, is brought to fruition in this work. It has the advantages of being lightweight, potentially cost-effective, self-tuning, has negligible dynamics, and most importantly (from a robustness perspective), it provides a colocated sensor/actuator pair. The transducer consists of a piezoceramic element which serves as both an actuator and a sensor and will be referred to in this work as a sensoriactuator. Simple, adaptive signal processing in conjunction with a voltage controlled amplifier, reference capacitor, and a common-mode rejection circuit extract the mechanical response from the total response of the piezoelectric sensoriactuator for sensing. The digital portion of the adaptive piezoelectric sensoriactuator merely serves to tune the circuit, avoiding the potentially destabilizing effects of introducing a digital delay in the signal path, when used for feedback control applications. Adaptive compensation of the sensoriactuator is necessary since the signal to noise ratio is typically greater than 40 dB, making it prohibitive to tune the circuit manually. In addition, the constitutive properties of piezoceramics vary with time and environment, necessitating that the circuit be periodically re-tuned. The analog portion of the hardware is based upon op-amp circuits and an AD632 analog multiplier chip, which serves as both a voltage controlled amplifier (VCA) and a common mode rejection (CMR) circuit. A single coefficient least-mean square (LMS) adaptive filter continuously adjusts the gain of the VCA circuit as necessary. Nonideal behavior of piezoceramics is discussed along with methods to counter the consequential deterioration in circuit performance. A multiple input multiple output (MIMO) implementation of the adaptive piezoelectric sensoriactuator is developed using orthogonal white noise training signals for each sensoriactuator. Two piezostructures were used to demonstrate and verify the adaptive piezoelectric sensoriactuator, a cantilevered beam and a simply-supported plate. The experimental open- loop results compare well with theory. A preliminary closed-loop rate controller applied to the cantilevered beam demonstrates simultaneous control and adaptation of the piezoelectric sensoriactuator. Lastly, [/cal H]2 optimal feedback Active Structural Acoustic Control (ASAC) is demonstrated using the adaptive piezoelectric sensoriactuators and the simply- supported plate test bed. A cost function is formulated based upon control effort and predicted radiated acoustic power. Radiation filters are created to predict acoustic power based on the self and mutual radiation efficiencies of the plate modes to be controlled. Both static output feedback and state-feedback compensation as well as dynamic (Linear Quadratic Gaussian) compensation are investigated and compared analytically. The importance of choosing an appropriate spatial aperture for the piezoceramic transducer for static compensation is discussed. Finally, multivariable Active Vibration Control (AVC) and ASAC are implemented experimentally on a simply-supported plate test bed using an array of four Adaptive Piezoelectric Sensoriactuators as the control sensors and actuators. Unfavorable high-frequency response from the given piezoceramic transducers required that dynamic, Linear Quadratic Gaussian (LQG) compensation be used to achieve good control performance.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Robust Optimal Adaptive Control Method with Large Adaptive Gain

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2009-01-01

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

An adaptive PID like controller using mix locally recurrent neural network for robotic manipulator with variable payload.

PubMed

Sharma, Richa; Kumar, Vikas; Gaur, Prerna; Mittal, A P

2016-05-01

Being complex, non-linear and coupled system, the robotic manipulator cannot be effectively controlled using classical proportional-integral-derivative (PID) controller. To enhance the effectiveness of the conventional PID controller for the nonlinear and uncertain systems, gains of the PID controller should be conservatively tuned and should adapt to the process parameter variations. In this work, a mix locally recurrent neural network (MLRNN) architecture is investigated to mimic a conventional PID controller which consists of at most three hidden nodes which act as proportional, integral and derivative node. The gains of the mix locally recurrent neural network based PID (MLRNNPID) controller scheme are initialized with a newly developed cuckoo search algorithm (CSA) based optimization method rather than assuming randomly. A sequential learning based least square algorithm is then investigated for the on-line adaptation of the gains of MLRNNPID controller. The performance of the proposed controller scheme is tested against the plant parameters uncertainties and external disturbances for both links of the two link robotic manipulator with variable payload (TL-RMWVP). The stability of the proposed controller is analyzed using Lyapunov stability criteria. A performance comparison is carried out among MLRNNPID controller, CSA optimized NNPID (OPTNNPID) controller and CSA optimized conventional PID (OPTPID) controller in order to establish the effectiveness of the MLRNNPID controller. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Advanced control of dissolved oxygen concentration in fed batch cultures during recombinant protein production.

PubMed

Kuprijanov, A; Gnoth, S; Simutis, R; Lübbert, A

2009-02-01

Design and experimental validation of advanced pO(2) controllers for fermentation processes operated in the fed-batch mode are described. In most situations, the presented controllers are able to keep the pO(2) in fermentations for recombinant protein productions exactly on the desired value. The controllers are based on the gain-scheduling approach to parameter-adaptive proportional-integral controllers. In order to cope with the most often appearing distortions, the basic gain-scheduling feedback controller was complemented with a feedforward control component. This feedforward/feedback controller significantly improved pO(2) control. By means of numerical simulations, the controller behavior was tested and its parameters were determined. Validation runs were performed with three Escherichia coli strains producing different recombinant proteins. It is finally shown that the new controller leads to significant improvements in the signal-to-noise ratio of other key process variables and, thus, to a higher process quality.

Thermal Inactivation of Desiccation-Adapted Salmonella spp. in Aged Chicken Litter

PubMed Central

Chen, Zhao; Diao, Junshu; Dharmasena, Muthu; Ionita, Claudia; Rieck, James

2013-01-01

Thermal inactivation of desiccation-adapted Salmonella spp. in aged chicken litter was investigated in comparison with that in a nonadapted control to examine potential cross-tolerance of desiccation-adapted cells to heat treatment. A mixture of four Salmonella serovars was inoculated into the finished compost with 20, 30, 40, and 50% moisture contents for a 24-h desiccation adaptation. Afterwards, the compost with desiccation-adapted cells was inoculated into the aged chicken litter with the same moisture content for heat treatments at 70, 75, 80, 85, and 150°C. Recovery media were used to allow heat-injured cells to resuscitate. A 5-log reduction in the number of the desiccation-adapted cells in aged chicken litter with a 20% moisture content required >6, >6, ∼4 to 5, and ∼3 to 4 h of exposure at 70, 75, 80, and 85°C, respectively. As a comparison, a 5-log reduction in the number of nonadapted control cells in the same chicken litter was achieved within ∼1.5 to 2, ∼1 to 1.5, ∼0.5 to 1, and <0.5 h at 70, 75, 80, and 85°C, respectively. The exposure time required to obtain a 5-log reduction in the number of desiccation-adapted cells gradually became shorter as temperature and moisture content were increased. At 150°C, desiccation-adapted Salmonella cells survived for 50 min in chicken litter with a 20% moisture content, whereas control cells were detectable by enrichment for only 10 min. Our results demonstrated that the thermal resistance of Salmonella in aged chicken litter was increased significantly when the cells were adapted to desiccation. This study also validated the effectiveness of thermal processing being used for producing chicken litter free of Salmonella contamination. PMID:24014540

Thermal inactivation of desiccation-adapted Salmonella spp. in aged chicken litter.

PubMed

Chen, Zhao; Diao, Junshu; Dharmasena, Muthu; Ionita, Claudia; Jiang, Xiuping; Rieck, James

2013-11-01

Thermal inactivation of desiccation-adapted Salmonella spp. in aged chicken litter was investigated in comparison with that in a nonadapted control to examine potential cross-tolerance of desiccation-adapted cells to heat treatment. A mixture of four Salmonella serovars was inoculated into the finished compost with 20, 30, 40, and 50% moisture contents for a 24-h desiccation adaptation. Afterwards, the compost with desiccation-adapted cells was inoculated into the aged chicken litter with the same moisture content for heat treatments at 70, 75, 80, 85, and 150°C. Recovery media were used to allow heat-injured cells to resuscitate. A 5-log reduction in the number of the desiccation-adapted cells in aged chicken litter with a 20% moisture content required >6, >6, ∼4 to 5, and ∼3 to 4 h of exposure at 70, 75, 80, and 85°C, respectively. As a comparison, a 5-log reduction in the number of nonadapted control cells in the same chicken litter was achieved within ∼1.5 to 2, ∼1 to 1.5, ∼0.5 to 1, and <0.5 h at 70, 75, 80, and 85°C, respectively. The exposure time required to obtain a 5-log reduction in the number of desiccation-adapted cells gradually became shorter as temperature and moisture content were increased. At 150°C, desiccation-adapted Salmonella cells survived for 50 min in chicken litter with a 20% moisture content, whereas control cells were detectable by enrichment for only 10 min. Our results demonstrated that the thermal resistance of Salmonella in aged chicken litter was increased significantly when the cells were adapted to desiccation. This study also validated the effectiveness of thermal processing being used for producing chicken litter free of Salmonella contamination.

A global bioheat model with self-tuning optimal regulation of body temperature using Hebbian feedback covariance learning.

PubMed

Ong, M L; Ng, E Y K

2005-12-01

In the lower brain, body temperature is continually being regulated almost flawlessly despite huge fluctuations in ambient and physiological conditions that constantly threaten the well-being of the body. The underlying control problem defining thermal homeostasis is one of great enormity: Many systems and sub-systems are involved in temperature regulation and physiological processes are intrinsically complex and intertwined. Thus the defining control system has to take into account the complications of nonlinearities, system uncertainties, delayed feedback loops as well as internal and external disturbances. In this paper, we propose a self-tuning adaptive thermal controller based upon Hebbian feedback covariance learning where the system is to be regulated continually to best suit its environment. This hypothesis is supported in part by postulations of the presence of adaptive optimization behavior in biological systems of certain organisms which face limited resources vital for survival. We demonstrate the use of Hebbian feedback covariance learning as a possible self-adaptive controller in body temperature regulation. The model postulates an important role of Hebbian covariance adaptation as a means of reinforcement learning in the thermal controller. The passive system is based on a simplified 2-node core and shell representation of the body, where global responses are captured. Model predictions are consistent with observed thermoregulatory responses to conditions of exercise and rest, and heat and cold stress. An important implication of the model is that optimal physiological behaviors arising from self-tuning adaptive regulation in the thermal controller may be responsible for the departure from homeostasis in abnormal states, e.g., fever. This was previously unexplained using the conventional "set-point" control theory.

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.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop.

PubMed

Ewing, Kate C; Fairclough, Stephen H; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed.

Evaluation of an Adaptive Game that Uses EEG Measures Validated during the Design Process as Inputs to a Biocybernetic Loop

PubMed Central

Ewing, Kate C.; Fairclough, Stephen H.; Gilleade, Kiel

2016-01-01

Biocybernetic adaptation is a form of physiological computing whereby real-time data streaming from the brain and body is used by a negative control loop to adapt the user interface. This article describes the development of an adaptive game system that is designed to maximize player engagement by utilizing changes in real-time electroencephalography (EEG) to adjust the level of game demand. The research consists of four main stages: (1) the development of a conceptual framework upon which to model the interaction between person and system; (2) the validation of the psychophysiological inference underpinning the loop; (3) the construction of a working prototype; and (4) an evaluation of the adaptive game. Two studies are reported. The first demonstrates the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to changing levels of game demand. These variables were then reformulated within the working biocybernetic control loop designed to maximize player engagement. The second study evaluated the performance of an adaptive game of Tetris with respect to system behavior and user experience. Important issues for the design and evaluation of closed-loop interfaces are discussed. PMID:27242486

Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting

NASA Technical Reports Server (NTRS)

Trujillo, Anna; Gregory, Irene

2013-01-01

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

Dynamic neural networks based on-line identification and control of high performance motor drives

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kotaru, Raj

1995-01-01

In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

Genome hypermethylation in Pinus silvestris of Chernobyl--a mechanism for radiation adaptation?

PubMed

Kovalchuk, Olga; Burke, Paula; Arkhipov, Andrey; Kuchma, Nikolaj; James, S Jill; Kovalchuk, Igor; Pogribny, Igor

2003-08-28

Adaptation is a complex process by which populations of organisms respond to long-term environmental stresses by permanent genetic change. Here we present data from the natural "open-field" radiation adaptation experiment after the Chernobyl accident and provide the first evidence of the involvement of epigenetic changes in adaptation of a eukaryote-Scots pine (Pinus silvestris), to chronic radiation exposure. We have evaluated global genome methylation of control and radiation-exposed pine trees using a method based on cleavage by a methylation-sensitive HpaII restriction endonuclease that leaves a 5' guanine overhang and subsequent single nucleotide extension with labeled [3H] dCTP. We have found that genomic DNA of exposed pine trees was considerably hypermethylated. Moreover, hypermethylation appeared to be dependent upon the radiation dose absorbed by the trees. Such hypermethylation may be viewed as a defense strategy of plants that prevents genome instability and reshuffling of the hereditary material, allowing survival in an extreme environment. Further studies are clearly needed to analyze in detail the involvement of DNA methylation and other epigenetic mechanisms in the complex process of radiation stress and adaptive response.

Cellular Factors Targeting APCs to Modulate Adaptive T Cell Immunity

PubMed Central

Do, Jeongsu; Min, Booki

2014-01-01

The fate of adaptive T cell immunity is determined by multiple cellular and molecular factors, among which the cytokine milieu plays the most important role in this process. Depending on the cytokines present during the initial T cell activation, T cells become effector cells that produce different effector molecules and execute adaptive immune functions. Studies thus far have primarily focused on defining how these factors control T cell differentiation by targeting T cells themselves. However, other non-T cells, particularly APCs, also express receptors for the factors and are capable of responding to them. In this review, we will discuss how APCs, by responding to those cytokines, influence T cell differentiation and adaptive immunity. PMID:25126585

A Feedfordward Adaptive Controller to Reduce the Imaging Time of Large-Sized Biological Samples with a SPM-Based Multiprobe Station

PubMed Central

Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel

2012-01-01

The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491

Robust control of accelerators

NASA Astrophysics Data System (ADS)

Joel, W.; Johnson, D.; Chaouki, Abdallah T.

1991-07-01

The problem of controlling the variations in the rf power system can be effectively cast as an application of modern control theory. Two components of this theory are obtaining a model and a feedback structure. The model inaccuracies influence the choice of a particular controller structure. Because of the modelling uncertainty, one has to design either a variable, adaptive controller or a fixed, robust controller to achieve the desired objective. The adaptive control scheme usually results in very complex hardware; and, therefore, shall not be pursued in this research. In contrast, the robust control method leads to simpler hardware. However, robust control requires a more accurate mathematical model of the physical process than is required by adaptive control. Our research at the Los Alamos National Laboratory (LANL) and the University of New Mexico (UNM) has led to the development and implementation of a new robust rf power feedback system. In this article, we report on our research progress. In section 1, the robust control problem for the rf power system and the philosophy adopted for the beginning phase of our research is presented. In section 2, the results of our proof-of-principle experiments are presented. In section 3, we describe the actual controller configuration that is used in LANL FEL physics experiments. The novelty of our approach is that the control hardware is implemented directly in rf. without demodulating, compensating, and then remodulating.

Effects of practice schedule and task specificity on the adaptive process of motor learning.

PubMed

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive self-organization of Bali's ancient rice terraces.

PubMed

Lansing, J Stephen; Thurner, Stefan; Chung, Ning Ning; Coudurier-Curveur, Aurélie; Karakaş, Çağil; Fesenmyer, Kurt A; Chew, Lock Yue

2017-06-20

Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers' decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers' decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human-natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.

The impact of occupational therapy and lifestyle interventions on older persons' health, well-being, and occupational adaptation.

PubMed

Johansson, Ann; Björklund, Anita

2016-01-01

The aim of this study was to investigate whether a four-month occupational based health-promoting programme for older persons living in community dwellings could maintain/improve their general health and well-being. Further, the aim was to explore whether the programme facilitated the older persons' occupational adaptation. The study had a quasi-experimental design, with a non-equivalent control group combined with semi-structured interviews. The intervention group comprised 22 participants, and the control group 18. Outcomes were measured using the Short Form 36, Life Satisfaction Index-Z and Meaningful Activity Participation Assessment. Content analysis, based on concepts from the Model of Occupational Adaptation, was used to analyse the interviews. The intervention group showed statistically significant improvements in general health variables such as vitality and mental health, and positive trends for psychological well-being. There were no statistically significant differences between the intervention group and the control group, but the groups were not fully matched. The qualitative analysis based on Occupational Adaptation pointed out social aspects as a compliment to the overall results. Participating in meaningful, challenging activities in different environments stimulates the occupational adaptation process; this is something occupational therapists could use to empower older persons to find their optimal occupational lives.

The functional basis of adaptive evolution in chemostats.

PubMed

Gresham, David; Hong, Jungeui

2015-01-01

Two of the central problems in biology are determining the molecular basis of adaptive evolution and understanding how cells regulate their growth. The chemostat is a device for culturing cells that provides great utility in tackling both of these problems: it enables precise control of the selective pressure under which organisms evolve and it facilitates experimental control of cell growth rate. The aim of this review is to synthesize results from studies of the functional basis of adaptive evolution in long-term chemostat selections using Escherichia coli and Saccharomyces cerevisiae. We describe the principle of the chemostat, provide a summary of studies of experimental evolution in chemostats, and use these studies to assess our current understanding of selection in the chemostat. Functional studies of adaptive evolution in chemostats provide a unique means of interrogating the genetic networks that control cell growth, which complements functional genomic approaches and quantitative trait loci (QTL) mapping in natural populations. An integrated approach to the study of adaptive evolution that accounts for both molecular function and evolutionary processes is critical to advancing our understanding of evolution. By renewing efforts to integrate these two research programs, experimental evolution in chemostats is ideally suited to extending the functional synthesis to the study of genetic networks. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

Adaptive fuzzy system for 3-D vision

NASA Technical Reports Server (NTRS)

Mitra, Sunanda

1993-01-01

An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

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

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Contribution of fronto-striatal regions to emotional valence and repetition under cognitive conflict.

PubMed

Chun, Ji-Won; Park, Hae-Jeong; Kim, Dai Jin; Kim, Eosu; Kim, Jae-Jin

2017-07-01

Conflict processing mediated by fronto-striatal regions may be influenced by emotional properties of stimuli. This study aimed to examine the effects of emotion repetition on cognitive control in a conflict-provoking situation. Twenty-one healthy subjects were scanned using functional magnetic resonance imaging while performing a sequential cognitive conflict task composed of emotional stimuli. The regional effects were analyzed according to the repetition or non-repetition of cognitive congruency and emotional valence between the preceding and current trials. Post-incongruence interference in error rate and reaction time was significantly smaller than post-congruence interference, particularly under repeated positive and non-repeated positive, respectively, and post-incongruence interference, compared to post-congruence interference, increased activity in the ACC, DLPFC, and striatum. ACC and DLPFC activities were significantly correlated with error rate or reaction time in some conditions, and fronto-striatal connections were related to the conflict processing heightened by negative emotion. These findings suggest that the repetition of emotional stimuli adaptively regulates cognitive control and the fronto-striatal circuit may engage in the conflict adaptation process induced by emotion repetition. Both repetition enhancement and repetition suppression of prefrontal activity may underlie the relationship between emotion and conflict adaptation. Copyright © 2017 Elsevier B.V. All rights reserved.

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

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

Chai, Tianyou; Jia, Yao; Wang, Hong

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperaturemore » are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.« less

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.

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

PubMed

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

2018-02-21

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

Modification of saccadic gain by reinforcement

PubMed Central

Paeye, Céline; Wallman, Josh

2011-01-01

Control of saccadic gain is often viewed as a simple compensatory process in which gain is adjusted over many trials by the postsaccadic retinal error, thereby maintaining saccadic accuracy. Here, we propose that gain might also be changed by a reinforcement process not requiring a visual error. To test this hypothesis, we used experimental paradigms in which retinal error was removed by extinguishing the target at the start of each saccade and either an auditory tone or the vision of the target on the fovea was provided as reinforcement after those saccades that met an amplitude criterion. These reinforcement procedures caused a progressive change in saccade amplitude in nearly all subjects, although the rate of adaptation differed greatly among subjects. When we reversed the contingencies and reinforced those saccades landing closer to the original target location, saccade gain changed back toward normal gain in most subjects. When subjects had saccades adapted first by reinforcement and a week later by conventional intrasaccadic step adaptation, both paradigms yielded similar degrees of gain changes and similar transfer to new amplitudes and to new starting positions of the target step as well as comparable rates of recovery. We interpret these changes in saccadic gain in the absence of postsaccadic retinal error as showing that saccade adaptation is not controlled by a single error signal. More generally, our findings suggest that normal saccade adaptation might involve general learning mechanisms rather than only specialized mechanisms for motor calibration. PMID:21525366

An Optimal Parameter Discretization Strategy for Multiple Model Adaptive Estimation and Control

DTIC Science & Technology

1989-12-01

Zicker . MMAE-Based Control with Space- Time Point Process Observations. IEEE Transactions on Aerospace and Elec- tronic Systems, AES-21 (3):292-300, 1985...Transactions of the Conference of Army Math- ematicians, Bethesda MD, 1982. (AD-POO1 033). 65. William L. Zicker . Pointing and Tracking of Particle

A Pilot-Scale Heat Recovery System for Computer Process Control Teaching and Research.

ERIC Educational Resources Information Center

Callaghan, P. J.; And Others

1988-01-01

Describes the experimental system and equipment including an interface box for displaying variables. Discusses features which make the circuit suitable for teaching and research in computing. Feedforward, decoupling, and adaptive control, examination of digital filtering, and a cascade loop are teaching experiments utilizing this rig. Diagrams and…

Mass Conflagration: An Analysis and Adaptation of the Shipboard Damage Control Organization

DTIC Science & Technology

1991-03-01

the span of control narrows, as each supervisor is able to better monitor the actions and environment of his subordinates. (6) Communciation and... computed decision is reached by the decision makers, often based on a prior formal doctrine or methodology. [Ref. 4:p. 364] While no decision process

Optimization of IBF parameters based on adaptive tool-path algorithm

NASA Astrophysics Data System (ADS)

Deng, Wen Hui; Chen, Xian Hua; Jin, Hui Liang; Zhong, Bo; Hou, Jin; Li, An Qi

2018-03-01

As a kind of Computer Controlled Optical Surfacing(CCOS) technology. Ion Beam Figuring(IBF) has obvious advantages in the control of surface accuracy, surface roughness and subsurface damage. The superiority and characteristics of IBF in optical component processing are analyzed from the point of view of removal mechanism. For getting more effective and automatic tool path with the information of dwell time, a novel algorithm is proposed in this thesis. Based on the removal functions made through our IBF equipment and the adaptive tool-path, optimized parameters are obtained through analysis the residual error that would be created in the polishing process. A Φ600 mm plane reflector element was used to be a simulation instance. The simulation result shows that after four combinations of processing, the surface accuracy of PV (Peak Valley) value and the RMS (Root Mean Square) value was reduced to 4.81 nm and 0.495 nm from 110.22 nm and 13.998 nm respectively in the 98% aperture. The result shows that the algorithm and optimized parameters provide a good theoretical for high precision processing of IBF.

Adaptive Flight Control for Aircraft Safety Enhancements

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Multi-Level Adaptive Techniques (MLAT) for singular-perturbation problems

NASA Technical Reports Server (NTRS)

Brandt, A.

1978-01-01

The multilevel (multigrid) adaptive technique, a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization is described. It provides very fast general solvers, together with adaptive, nearly optimal discretization schemes. In the process, boundary layers are automatically either resolved or skipped, depending on a control function which expresses the computational goal. The global error decreases exponentially as a function of the overall computational work, in a uniform rate independent of the magnitude of the singular-perturbation terms. The key is high-order uniformly stable difference equations, and uniformly smoothing relaxation schemes.

Implications of Childhood Experiences for the Health and Adaptation of Lesbian, Gay, and Bisexual Individuals: Sensitivity to Developmental Process in Future Research

PubMed Central

Rosario, Margaret

2015-01-01

The empirical literature on lesbian, gay, and bisexual (LGB) individuals has predominantly focused on sexual-orientation disparities between LGB and heterosexual individuals on health and adaptation, as well as on the role of gay-related or minority stress in the health and adaptation of LGB individuals. Aside from demographic control variables, the initial predictor is a marker of sexual orientation or LGB-related experience (e.g., minority stress). Missing are potential strengths and vulnerabilities that LGB individuals develop over time and bring to bear on their sexual identity development and other LGB-related experiences. Those strengths and vulnerabilities may have profound consequences for the sexual identity development, health, and adaptation of LGB individuals. Here, I focus on one such set of strengths and vulnerabilities derived from attachment. I conclude by emphasizing the importance of attachment in the lives of LGB individuals and the need to identify other developmental processes that may be equally consequential. PMID:26900586

Culturally adapted versus standard exposure treatment for phobic Asian Americans: Treatment efficacy, moderators, and predictors.

PubMed

Pan, David; Huey, Stanley J; Hernandez, Dominica

2011-01-01

This study is a 6-month follow-up of a randomized pilot evaluation of standard one-session treatment (OST-S) versus culturally adapted OST (OST-CA) with phobic Asian Americans. OST-CA included seven cultural adaptations drawn from prior research with East Asians and Asian Americans. Results from 1-week and 6-month follow-up show that both OST-S and OST-CA were effective at reducing phobic symptoms compared with self-help control. Moreover, OST-CA was superior to OST-S for several outcomes. For catastrophic thinking and general fear, moderator analyses indicated that low-acculturation Asian Americans benefitted more from OST-CA than OST-S, whereas both treatments were equally effective for high-acculturation participants. Although cultural process factors (e.g., facilitating emotional control, exploiting the vertical therapist-client relationship) and working alliance were predictive of positive outcomes, they did not mediate treatment effects. This study offers a potential model for evaluating cultural adaptation effects, as well as the mechanisms that account for such effects.

Evolutionary online behaviour learning and adaptation in real robots.

PubMed

Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne

2017-07-01

Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.

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

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2018-01-01

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

Panarchy

USGS Publications Warehouse

Garmestani, Ahjond S.; Allen, Craig R.; El-Shaarawi, Abdel H.; Piegorsch, Walter W.

2012-01-01

Panarchy is the term coined to describe hierarchical systems where control is not only top down, as typically considered, but also bottom up. A panarchy is composed of adaptive cycles, and an adaptive cycle describes the processes of development and decay in a system. Complex systems self-organize into hierarchies because this structure limits the possible spread of destructive phenomena (e.g., forest fires, epidemics) that could result in catastrophic system failure. Thus, hierarchical organization enhances the resilience of complex systems.

Effects of hypoxia on sympathetic neural control in humans

NASA Technical Reports Server (NTRS)

Smith, M. L.; Muenter, N. K.

2000-01-01

This special issue is principally focused on the time domain of the adaptive mechanisms of ventilatory responses to short-term, long-term and intermittent hypoxia. The purpose of this review is to summarize the limited literature on the sympathetic neural responses to sustained or intermittent hypoxia in humans and attempt to discern the time domain of these responses and potential adaptive processes that are evoked during short and long-term exposures to hypoxia.

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

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

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

NASA Technical Reports Server (NTRS)

Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

2010-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Vibration suppression for large scale adaptive truss structures using direct output feedback control

NASA Technical Reports Server (NTRS)

Lu, Lyan-Ywan; Utku, Senol; Wada, Ben K.

1993-01-01

In this article, the vibration control of adaptive truss structures, where the control actuation is provided by length adjustable active members, is formulated as a direct output feedback control problem. A control method named Model Truncated Output Feedback (MTOF) is presented. The method allows the control feedback gain to be determined in a decoupled and truncated modal space in which only the critical vibration modes are retained. The on-board computation required by MTOF is minimal; thus, the method is favorable for the applications of vibration control of large scale structures. The truncation of the modal space inevitably introduces spillover effect during the control process. In this article, the effect is quantified in terms of active member locations, and it is shown that the optimal placement of active members, which minimizes the spillover effect (and thus, maximizes the control performance) can be sought. The problem of optimally selecting the locations of active members is also treated.

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

NASA Technical Reports Server (NTRS)

Salazar, George A. (Inventor); Haynes, Dena S. (Inventor); Sommers, Marc J. (Inventor)

1998-01-01

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

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

Luo, Shaohua; School of Automation, Chongqing University, Chongqing 400044; Sun, Quanping

This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Puttingmore » tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.« less

Kalman filter based control for Adaptive Optics

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

Dynamic adjustments of cognitive control during economic decision making.

PubMed

Soutschek, Alexander; Schubert, Torsten

2014-10-01

Decision making in the Ultimatum game requires the resolution of conflicts between economic self-interest and fairness intuitions. Since cognitive control processes play an important role in conflict resolution, the present study examined how control processes that are triggered by conflicts between fairness and self-interest in unfair offers affect subsequent decisions in the Ultimatum game. Our results revealed that more unfair offers were accepted following previously unfair, compared to previously fair offers. Interestingly, the magnitude of this conflict adaptation effect correlated with the individual subjects' focus on economic self-interest. We concluded that conflicts between fairness and self-interest trigger cognitive control processes, which reinforce the focus on the current task goal. Copyright © 2014 Elsevier B.V. All rights reserved.

Thirty Meter Telescope (TMT) Narrow Field Infrared Adaptive Optics System (NFIRAOS) real-time controller preliminary architecture

NASA Astrophysics Data System (ADS)

Kerley, Dan; Smith, Malcolm; Dunn, Jennifer; Herriot, Glen; Véran, Jean-Pierre; Boyer, Corinne; Ellerbroek, Brent; Gilles, Luc; Wang, Lianqi

2016-08-01

The Narrow Field Infrared Adaptive Optics System (NFIRAOS) is the first light Adaptive Optics (AO) system for the Thirty Meter Telescope (TMT). A critical component of NFIRAOS is the Real-Time Controller (RTC) subsystem which provides real-time wavefront correction by processing wavefront information to compute Deformable Mirror (DM) and Tip/Tilt Stage (TTS) commands. The National Research Council of Canada - Herzberg (NRC-H), in conjunction with TMT, has developed a preliminary design for the NFIRAOS RTC. The preliminary architecture for the RTC is comprised of several Linux-based servers. These servers are assigned various roles including: the High-Order Processing (HOP) servers, the Wavefront Corrector Controller (WCC) server, the Telemetry Engineering Display (TED) server, the Persistent Telemetry Storage (PTS) server, and additional testing and spare servers. There are up to six HOP servers that accept high-order wavefront pixels, and perform parallelized pixel processing and wavefront reconstruction to produce wavefront corrector error vectors. The WCC server performs low-order mode processing, and synchronizes and aggregates the high-order wavefront corrector error vectors from the HOP servers to generate wavefront corrector commands. The Telemetry Engineering Display (TED) server is the RTC interface to TMT and other subsystems. The TED server receives all external commands and dispatches them to the rest of the RTC servers and is responsible for aggregating several offloading and telemetry values that are reported to other subsystems within NFIRAOS and TMT. The TED server also provides the engineering GUIs and real-time displays. The Persistent Telemetry Storage (PTS) server contains fault tolerant data storage that receives and stores telemetry data, including data for Point-Spread Function Reconstruction (PSFR).

Mass production of bacterial communities adapted to the degradation of volatile organic compounds (TEX).

PubMed

Lapertot, Miléna; Seignez, Chantal; Ebrahimi, Sirous; Delorme, Sandrine; Peringer, Paul

2007-06-01

This study focuses on the mass cultivation of bacteria adapted to the degradation of a mixture composed of toluene, ethylbenzene, o-, m- and p-xylenes (TEX). For the cultivation process Substrate Pulse Batch (SPB) technique was adapted under well-automated conditions. The key parameters to be monitored were handled by LabVIEW software including, temperature, pH, dissolved oxygen and turbidity. Other parameters, such as biomass, ammonium or residual substrate concentrations needed offline measurements. SPB technique has been successfully tested experimentally on TEX. The overall behavior of the mixed bacterial population was observed and discussed along the cultivation process. Carbon and nitrogen limitations were shown to affect the integrity of the bacterial cells as well as their production of exopolymeric substances (EPS). Average productivity and yield values successfully reached the industrial specifications, which were 0.45 kg(DW)m(-3) d(-1) and 0.59 g(DW)g (C) (-1) , respectively. Accuracy and reproducibility of the obtained results present the controlled SPB process as a feasible technique.

Adapting to an initial self-regulatory task cancels the ego depletion effect.

PubMed

Dang, Junhua; Dewitte, Siegfried; Mao, Lihua; Xiao, Shanshan; Shi, Yucai

2013-09-01

The resource-based model of self-regulation provides a pessimistic view of self-regulation that people are destined to lose their self-control after having engaged in any act of self-regulation because these acts deplete the limited resource that people need for successful self-regulation. The cognitive control theory, however, offers an alternative explanation and suggests that the depletion effect reflects switch costs between different cognitive control processes recruited to deal with demanding tasks. This account implies that the depletion effect will not occur once people have had the opportunity to adapt to the self-regulatory task initially engaged in. Consistent with this idea, the present study showed that engaging in a demanding task led to performance deficits on a subsequent self-regulatory task (i.e. the depletion effect) only when the initial demanding task was relatively short but not when it was long enough for participants to adapt. Our results were unrelated to self-efficacy, mood, and motivation. Copyright © 2013 Elsevier Inc. All rights reserved.

Use of adaptive cruise control functions on motorways and urban roads: Changes over time in an on-road study.

PubMed

Pereira, Marta; Beggiato, Matthias; Petzoldt, Tibor

2015-09-01

The study aimed at investigating how drivers use Adaptive Cruise Control and its functions in distinct road environments and to verify if changes occur over time. Fifteen participants were invited to drive a vehicle equipped with a Stop & Go Adaptive Cruise Control system on nine occasions. The course remained the same for each test run and included roads on urban and motorway environments. Results showed significant effect of experience for ACC usage percentage, and selection of the shortest time headway value in the urban road environment. This indicates that getting to know a system is not a homogenous process, as mastering the use of all the system's functions can take differing lengths of time in distinct road environments. Results can be used not only for the development of the new generation of systems that integrate ACC functionalities but also for determining the length of training required to operate an ACC system. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

A miniature high-efficiency fully digital adaptive voltage scaling buck converter

NASA Astrophysics Data System (ADS)

Li, Hangbiao; Zhang, Bo; Luo, Ping; Zhen, Shaowei; Liao, Pengfei; He, Yajuan; Li, Zhaoji

2015-09-01

A miniature high-efficiency fully digital adaptive voltage scaling (AVS) buck converter is proposed in this paper. The pulse skip modulation with flexible duty cycle (FD-PSM) is used in the AVS controller, which simplifies the circuit architecture (<170 gates) and greatly saves the die area and the power consumption. The converter is implemented in a 0.13-μm one-poly-eight-metal (1P8 M) complementary metal oxide semiconductor process and the active on-chip area of the controller is only 0.003 mm2, which is much smaller. The measurement results show that when the operating frequency of the digital load scales dynamically from 25.6 MHz to 112.6 MHz, the supply voltage of which can be scaled adaptively from 0.84 V to 1.95 V. The controller dissipates only 17.2 μW, while the supply voltage of the load is 1 V and the operating frequency is 40 MHz.

Experimental evaluation of shape memory alloy actuation technique in adaptive antenna design concepts

NASA Astrophysics Data System (ADS)

Kefauver, W. Neill; Carpenter, Bernie F.

1994-09-01

Creation of an antenna system that could autonomously adapt contours of reflecting surfaces to compensate for structural loads induced by a variable environment would maximize performance of space-based communication systems. Design of such a system requires the comprehensive development and integration of advanced actuator, sensor, and control technologies. As an initial step in this process, a test has been performed to assess the use of a shape memory alloy as a potential actuation technique. For this test, an existing, offset, cassegrain antenna system was retrofit with a subreflector equipped with shape memory alloy actuators for surface contour control. The impacts that the actuators had on both the subreflector contour and the antenna system patterns were measured. The results of this study indicate the potential for using shape memory alloy actuation techniques to adaptively control antenna performance; both variations in gain and beam steering capabilities were demonstrated. Future development effort is required to evolve this potential into a useful technology for satellite applications.

Experimental evaluation of shape memory alloy actuation technique in adaptive antenna design concepts

NASA Technical Reports Server (NTRS)

Kefauver, W. Neill; Carpenter, Bernie F.

1994-01-01

Creation of an antenna system that could autonomously adapt contours of reflecting surfaces to compensate for structural loads induced by a variable environment would maximize performance of space-based communication systems. Design of such a system requires the comprehensive development and integration of advanced actuator, sensor, and control technologies. As an initial step in this process, a test has been performed to assess the use of a shape memory alloy as a potential actuation technique. For this test, an existing, offset, cassegrain antenna system was retrofit with a subreflector equipped with shape memory alloy actuators for surface contour control. The impacts that the actuators had on both the subreflector contour and the antenna system patterns were measured. The results of this study indicate the potential for using shape memory alloy actuation techniques to adaptively control antenna performance; both variations in gain and beam steering capabilities were demonstrated. Future development effort is required to evolve this potential into a useful technology for satellite applications.

Marginal and internal fit of curved anterior CAD/CAM-milled zirconia fixed dental prostheses: an in-vitro study.

PubMed

Büchi, Dominik L; Ebler, Sabine; Hämmerle, Christoph H F; Sailer, Irena

2014-01-01

To test whether or not different types of CAD/CAM systems, processing zirconia in the densely and in the pre-sintered stage, lead to differences in the accuracy of 4-unit anterior fixed dental prosthesis (FDP) frameworks, and to evaluate the efficiency. 40 curved anterior 4-unit FDP frameworks were manufactured with four different CAD/CAM systems: DCS Precident (DCS) (control group), Cercon (DeguDent) (test group 1), Cerec InLab (Sirona) (test group 2), Kavo Everest (Kavo) (test group 3). The DCS System was chosen as the control group because the zirconia frameworks are processed in its densely sintered stage and there is no shrinkage of the zirconia during the manufacturing process. The initial fit of the frameworks was checked and adjusted to a subjectively similar level of accuracy by one dental technician, and the time taken for this was recorded. After cementation, the frameworks were embedded into resin and the abutment teeth were cut in mesiodistal and orobuccal directions in four specimens. The thickness of the cement gap was measured at 50× (internal adaptation) and 200× (marginal adaptation) magnification. The measurement of the accuracy was performed at four sites. Site 1: marginal adaptation, the marginal opening at the point of closest perpendicular approximation between the die and framework margin. Site 2: Internal adaptation at the chamfer. Site 3: Internal adaptation at the axial wall. Site 4: Internal adaptation in the occlusal area. The data were analyzed descriptively using the ANOVA and Bonferroni/ Dunn tests. The mean marginal adaptation (site 1) of the control group was 107 ± 26 μm; test group 1, 140 ± 26 μm; test group 2, 104 ± 40 μm; and test group 3, 95 ± 31 μm. Test group 1 showed a tendency to exhibit larger marginal gaps than the other groups, however, this difference was only significant when test groups 1 and 3 were compared (P = .0022; Bonferroni/Dunn test). Significantly more time was needed for the adjustment of the frameworks of test group 1 compared to the other test groups and the control group (21.1 min vs 3.8 min) (P < .0001; Bonferroni/Dunn test). For the adjustment of the frameworks of test groups 2 and 3, the same time was needed as for the frameworks of the control group. No differences of the framework accuracy resulting from the different CAM and CAD/CAM procedures were found; however, only after adjustment of the fit by an experienced dental technician. Hence, the influence of a manual correction of the fit was crucial, and the efforts differed for the tested systems. The CAM system led to lower initial accuracy of the frameworks than the CAD/CAM systems, which may be crucial for the dental laboratory. The stage of the zirconia materials used for the different CAD/CAM procedures, ie presintered or densely sintered, exhibited no influence.

Efficient community-based control strategies in adaptive networks

NASA Astrophysics Data System (ADS)

Yang, Hui; Tang, Ming; Zhang, Hai-Feng

2012-12-01

Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible-infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible-infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans.

Nursing Approach Based on Roy Adaptation Model in a Patient Undergoing Breast Conserving Surgery for Breast Cancer.

PubMed

Ursavaş, Figen Erol; Karayurt, Özgül; İşeri, Özge

2014-07-01

The use of models in nursing provides nurses to focus on the role of nursing and its applications rather than medical practice. In addition, it helps patient care to be systematic, purposeful, controlled and effective. One of the commonly used models in nursing is Roy Adaptation Model. According to Roy adaptation model, the aim of nursing is to increase compliance and life expectancy. Roy Adaptation Model evaluates the patient in physiologic mode, self-concept mode, role function mode and interdependence mode aiming to provide holistic care. This article describes the use of Roy Adaptation Model in the care of a patient who has been diagnosed with breast cancer and had breast-conserving surgery. Patient data was evaluated in the four modes of Roy adaptation model (physiologic, self-concept, role function, and interdependence modes) and the nursing process was applied.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Adaptive design of visual perception experiments

NASA Astrophysics Data System (ADS)

O'Connor, John D.; Hixson, Jonathan; Thomas, James M., Jr.; Peterson, Matthew S.; Parasuraman, Raja

2010-04-01

Meticulous experimental design may not always prevent confounds from affecting experimental data acquired during visual perception experiments. Although experimental controls reduce the potential effects of foreseen sources of interference, interaction, or noise, they are not always adequate for preventing the confounding effects of unforeseen forces. Visual perception experimentation is vulnerable to unforeseen confounds because of the nature of the associated cognitive processes involved in the decision task. Some confounds are beyond the control of experimentation, such as what a participant does immediately prior to experimental participation, or the participant's attitude or emotional state. Other confounds may occur through ignorance of practical control methods on the part of the experiment's designer. The authors conducted experiments related to experimental fatigue and initially achieved significant results that were, upon re-examination, attributable to a lack of adequate controls. Re-examination of the original results and the processes and events that led to them yielded a second experimental design with more experimental controls and significantly different results. The authors propose that designers of visual perception experiments can benefit from planning to use a test-fix-test or adaptive experimental design cycle, so that unforeseen confounds in the initial design can be remedied.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Exponential parameter and tracking error convergence guarantees for adaptive controllers without persistency of excitation

NASA Astrophysics Data System (ADS)

Chowdhary, Girish; Mühlegg, Maximilian; Johnson, Eric

2014-08-01

In model reference adaptive control (MRAC) the modelling uncertainty is often assumed to be parameterised with time-invariant unknown ideal parameters. The convergence of parameters of the adaptive element to these ideal parameters is beneficial, as it guarantees exponential stability, and makes an online learned model of the system available. Most MRAC methods, however, require persistent excitation of the states to guarantee that the adaptive parameters converge to the ideal values. Enforcing PE may be resource intensive and often infeasible in practice. This paper presents theoretical analysis and illustrative examples of an adaptive control method that leverages the increasing ability to record and process data online by using specifically selected and online recorded data concurrently with instantaneous data for adaptation. It is shown that when the system uncertainty can be modelled as a combination of known nonlinear bases, simultaneous exponential tracking and parameter error convergence can be guaranteed if the system states are exciting over finite intervals such that rich data can be recorded online; PE is not required. Furthermore, the rate of convergence is directly proportional to the minimum singular value of the matrix containing online recorded data. Consequently, an online algorithm to record and forget data is presented and its effects on the resulting switched closed-loop dynamics are analysed. It is also shown that when radial basis function neural networks (NNs) are used as adaptive elements, the method guarantees exponential convergence of the NN parameters to a compact neighbourhood of their ideal values without requiring PE. Flight test results on a fixed-wing unmanned aerial vehicle demonstrate the effectiveness of the method.

Acute alcohol intoxication impairs segmental body alignment in upright standing.

PubMed

Hafstrom, A; Patel, M; Modig, F; Magnusson, M; Fransson, P A

2014-01-01

Balance control when standing upright is a complex process requiring input from several partly independent mechanisms such as coordination, feedback and feedforward control, and adaptation. Acute alcohol intoxication from ethanol is recognized as a major contributor to accidental falls requiring medical care. This study aimed to investigate if intoxication at 0.06 and 0.10% blood alcohol concentration affected body alignment. Mean angular positions of the head, shoulder, hip, and knee were measured with 3D-motion analysis and compared with the ankle position in 25 healthy adults during standing with or without perturbations, and with eyes open or closed. Alcohol intoxication had significant effects on body alignment during perturbed and unperturbed stance, and on adaptation to perturbations. It induced a significantly more posterior alignment of the knees and shoulders, and a tendency for a more posterior and left deviated head alignment in perturbed stance than when sober. The impact of alcohol intoxication was most apparent on the knee alignment, where availability of visual information deteriorated the adaptation to perturbations. Thus, acute alcohol intoxication resulted in inadequate balance control strategies with increased postural rigidity and impaired adaptation to perturbations. These factors probably contribute to the increased risk of falling when intoxicated with alcohol.

Neural communication patterns underlying conflict detection, resolution, and adaptation.

PubMed

Oehrn, Carina R; Hanslmayr, Simon; Fell, Juergen; Deuker, Lorena; Kremers, Nico A; Do Lam, Anne T; Elger, Christian E; Axmacher, Nikolai

2014-07-30

In an ever-changing environment, selecting appropriate responses in conflicting situations is essential for biological survival and social success and requires cognitive control, which is mediated by dorsomedial prefrontal cortex (DMPFC) and dorsolateral prefrontal cortex (DLPFC). How these brain regions communicate during conflict processing (detection, resolution, and adaptation), however, is still unknown. The Stroop task provides a well-established paradigm to investigate the cognitive mechanisms mediating such response conflict. Here, we explore the oscillatory patterns within and between the DMPFC and DLPFC in human epilepsy patients with intracranial EEG electrodes during an auditory Stroop experiment. Data from the DLPFC were obtained from 12 patients. Thereof four patients had additional DMPFC electrodes available for interaction analyses. Our results show that an early θ (4-8 Hz) modulated enhancement of DLPFC γ-band (30-100 Hz) activity constituted a prerequisite for later successful conflict processing. Subsequent conflict detection was reflected in a DMPFC θ power increase that causally entrained DLPFC θ activity (DMPFC to DLPFC). Conflict resolution was thereafter completed by coupling of DLPFC γ power to DMPFC θ oscillations. Finally, conflict adaptation was related to increased postresponse DLPFC γ-band activity and to θ coupling in the reverse direction (DLPFC to DMPFC). These results draw a detailed picture on how two regions in the prefrontal cortex communicate to resolve cognitive conflicts. In conclusion, our data show that conflict detection, control, and adaptation are supported by a sequence of processes that use the interplay of θ and γ oscillations within and between DMPFC and DLPFC. Copyright © 2014 the authors 0270-6474/14/3410438-15$15.00/0.

Context-specific attentional sampling: Intentional control as a pre-requisite for contextual control.

PubMed

Brosowsky, Nicholaus P; Crump, Matthew J C

2016-08-01

Recent work suggests that environmental cues associated with previous attentional control settings can rapidly and involuntarily adjust attentional priorities. The current study tests predictions from adaptive-learning and memory-based theories of contextual control about the role of intentions for setting attentional priorities. To extend the empirical boundaries of contextual control phenomena, and to determine whether theoretical principles of contextual control are generalizable we used a novel bi-dimensional stimulus sampling task. Subjects viewed briefly presented arrays of letters and colors presented above or below fixation, and identified specific stimuli according to a dimensional (letter or color) and positional cue. Location was predictive of the cued dimension, but not the position or identity. In contrast to previous findings, contextual control failed to develop through automatic, adaptive-learning processes. Instead, previous experience with intentionally changing attentional sampling priorities between different contexts was required for contextual control to develop. Copyright © 2016 Elsevier Inc. All rights reserved.

Protocol and practice in the adaptive management of waterfowl harvests

USGS Publications Warehouse

Johnson, F.; Williams, K.

1999-01-01

Waterfowl harvest management in North America, for all its success, historically has had several shortcomings, including a lack of well-defined objectives, a failure to account for uncertain management outcomes, and inefficient use of harvest regulations to understand the effects of management. To address these and other concerns, the U.S. Fish and Wildlife Service began implementation of adaptive harvest management in 1995. Harvest policies are now developed using a Markov decision process in which there is an explicit accounting for uncontrolled environmental variation, partial controllability of harvest, and structural uncertainty in waterfowl population dynamics. Current policies are passively adaptive, in the sense that any reduction in structural uncertainty is an unplanned by-product of the regulatory process. A generalization of the Markov decision process permits the calculation of optimal actively adaptive policies, but it is not yet clear how state-specific harvest actions differ between passive and active approaches. The Markov decision process also provides managers the ability to explore optimal levels of aggregation or "management scale" for regulating harvests in a system that exhibits high temporal, spatial, and organizational variability. Progress in institutionalizing adaptive harvest management has been remarkable, but some managers still perceive the process as a panacea, while failing to appreciate the challenges presented by this more explicit and methodical approach to harvest regulation. Technical hurdles include the need to develop better linkages between population processes and the dynamics of landscapes, and to model the dynamics of structural uncertainty in a more comprehensive fashion. From an institutional perspective, agreement on how to value and allocate harvests continues to be elusive, and there is some evidence that waterfowl managers have overestimated the importance of achievement-oriented factors in setting hunting regulations. Indeed, it is these unresolved value judgements, and the lack of an effective structure for organizing debate, that present the greatest threat to adaptive harvest management as a viable means for coping with management uncertainty. Copyright ?? 1999 by The Resilience Alliance.

Gunslinger Effect and Müller-Lyer Illusion: Examining Early Visual Information Processing for Late Limb-Target Control.

PubMed

Roberts, James W; Lyons, James; Garcia, Daniel B L; Burgess, Raquel; Elliott, Digby

2017-07-01

The multiple process model contends that there are two forms of online control for manual aiming: impulse regulation and limb-target control. This study examined the impact of visual information processing for limb-target control. We amalgamated the Gunslinger protocol (i.e., faster movements following a reaction to an external trigger compared with the spontaneous initiation of movement) and Müller-Lyer target configurations into the same aiming protocol. The results showed the Gunslinger effect was isolated at the early portions of the movement (peak acceleration and peak velocity). Reacted aims reached a longer displacement at peak deceleration, but no differences for movement termination. The target configurations manifested terminal biases consistent with the illusion. We suggest the visual information processing demands imposed by reacted aims can be adapted by integrating early feedforward information for limb-target control.

Opsin1-2, G(q)α and arrestin levels at Limulus rhabdoms are controlled by diurnal light and a circadian clock.

PubMed

Battelle, Barbara-Anne; Kempler, Karen E; Parker, Alexander K; Gaddie, Cristina D

2013-05-15

Dark and light adaptation in photoreceptors involve multiple processes including those that change protein concentrations at photosensitive membranes. Light- and dark-adaptive changes in protein levels at rhabdoms have been described in detail in white-eyed Drosophila maintained under artificial light. Here we tested whether protein levels at rhabdoms change significantly in the highly pigmented lateral eyes of wild-caught Limulus polyphemus maintained in natural diurnal illumination and whether these changes are under circadian control. We found that rhabdomeral levels of opsins (Ops1-2), the G protein activated by rhodopsin (G(q)α) and arrestin change significantly from day to night and that nighttime levels of each protein at rhabdoms are significantly influenced by signals from the animal's central circadian clock. Clock input at night increases Ops1-2 and G(q)α and decreases arrestin levels at rhabdoms. Clock input is also required for a rapid decrease in rhabdomeral Ops1-2 beginning at sunrise. We found further that dark adaptation during the day and the night are not equivalent. During daytime dark adaptation, when clock input is silent, the increase of Ops1-2 at rhabdoms is small and G(q)α levels do not increase. However, increases in Ops1-2 and G(q)α at rhabdoms are enhanced during daytime dark adaptation by treatments that elevate cAMP in photoreceptors, suggesting that the clock influences dark-adaptive increases in Ops1-2 and G(q)α at Limulus rhabdoms by activating cAMP-dependent processes. The circadian regulation of Ops1-2 and G(q)α levels at rhabdoms probably has a dual role: to increase retinal sensitivity at night and to protect photoreceptors from light damage during the day.

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

PubMed

McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

2015-07-15

A key feature of neural networks is their ability to rapidly adjust their function, including signal gain and temporal dynamics, in response to changes in sensory inputs. These adjustments are thought to be important for optimizing the sensitivity of the system, yet their mechanisms remain poorly understood. We studied adaptive changes in temporal integration in direction-selective cells in macaque primary visual cortex, where specific hypotheses have been proposed to account for rapid adaptation. By independently stimulating direction-specific channels, we found that the control of temporal integration of motion at one direction was independent of motion signals driven at the orthogonal direction. We also found that individual neurons can simultaneously support two different profiles of temporal integration for motion in orthogonal directions. These findings rule out a broad range of adaptive mechanisms as being key to the control of temporal integration, including untuned normalization and nonlinearities of spike generation and somatic adaptation in the recorded direction-selective cells. Such mechanisms are too broadly tuned, or occur too far downstream, to explain the channel-specific and multiplexed temporal integration that we observe in single neurons. Instead, we are compelled to conclude that parallel processing pathways are involved, and we demonstrate one such circuit using a computer model. This solution allows processing in different direction/orientation channels to be separately optimized and is sensible given that, under typical motion conditions (e.g., translation or looming), speed on the retina is a function of the orientation of image components. Many neurons in visual cortex are understood in terms of their spatial and temporal receptive fields. It is now known that the spatiotemporal integration underlying visual responses is not fixed but depends on the visual input. For example, neurons that respond selectively to motion direction integrate signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales. Copyright © 2015 the authors 0270-6474/15/3510268-13$15.00/0.

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics

PubMed Central

Zou, Weiyao; Burns, Stephen A.

2012-01-01

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. PMID:22441462

Testing of Lagrange multiplier damped least-squares control algorithm for woofer-tweeter adaptive optics.

PubMed

Zou, Weiyao; Burns, Stephen A

2012-03-20

A Lagrange multiplier-based damped least-squares control algorithm for woofer-tweeter (W-T) dual deformable-mirror (DM) adaptive optics (AO) is tested with a breadboard system. We show that the algorithm can complementarily command the two DMs to correct wavefront aberrations within a single optimization process: the woofer DM correcting the high-stroke, low-order aberrations, and the tweeter DM correcting the low-stroke, high-order aberrations. The optimal damping factor for a DM is found to be the median of the eigenvalue spectrum of the influence matrix of that DM. Wavefront control accuracy is maximized with the optimized control parameters. For the breadboard system, the residual wavefront error can be controlled to the precision of 0.03 μm in root mean square. The W-T dual-DM AO has applications in both ophthalmology and astronomy. © 2012 Optical Society of America

Rapid Prototyping of Slot Die Devices for Roll to Roll Production of EL Fibers

PubMed Central

Bellingham, Alyssa; Bromhead, Nicholas; Fontecchio, Adam

2017-01-01

There is a growing interest in fibers supporting optoelectrical properties for textile and wearable display applications. Solution-processed electroluminescent (EL) material systems can be continuously deposited onto fiber or yarn substrates in a roll-to-roll process, making it easy to scale manufacturing. It is important to have precise control over layer deposition to achieve uniform and reliable light emission from these EL fibers. Slot-die coating offers this control and increases the rate of EL fiber production. Here, we report a highly adaptable, cost-effective 3D printing model for developing slot dies used in automatic coating systems. The resulting slot-die coating system enables rapid, reliable production of alternating current powder-based EL (ACPEL) fibers and can be adapted for many material systems. The benefits of this system over dip-coating for roll-to-roll production of EL fibers are demonstrated in this work. PMID:28772954

An evaluation of Admedus' tissue engineering process-treated (ADAPT) bovine pericardium patch (CardioCel) for the repair of cardiac and vascular defects.

PubMed

Strange, Geoff; Brizard, Christian; Karl, Tom R; Neethling, Leon

2015-03-01

Tissue engineers have been seeking the 'Holy Grail' solution to calcification and cytotoxicity of implanted tissue for decades. Tissues with all of the desired qualities for surgical repair of congenital heart disease (CHD) are lacking. An anti-calcification tissue engineering process (ADAPT TEP) has been developed and applied to bovine pericardium (BP) tissue (CardioCel, AdmedusRegen Pty Ltd, Perth, WA, Australia) to eliminate cytotoxicity, improve resistance to acute and chronic inflammation, reduce calcification and facilitate controlled tissue remodeling. Clinical data in pediatric patients, and additional pre-market authorized prescriber data demonstrate that CardioCel performs extremely well in the short term and is safe and effective for a range of congenital heart deformations. These data are supported by animal studies which have shown no more than normal physiologic levels of calcification, with good durability, biocompatibility and controlled healing.

The circadian clock controls toll-like receptor 9-mediated innate and adaptive immunity

PubMed Central

Silver, Adam C.; Arjona, Alvaro; Walker, Wendy E.; Fikrig, Erol

2012-01-01

Circadian rhythms refer to biologic processes that oscillate with a period of approximately 24 hours. These rhythms are sustained by a molecular clock and provide a temporal matrix that ensures the coordination of homeostatic processes with the periodicity of environmental challenges. We demonstrate the circadian molecular clock controls the expression and function of toll like receptor 9 (TLR9). In a vaccination model using TLR9 ligand as adjuvant, mice immunized at the time of enhanced TLR9 responsiveness presented weeks later with an improved adaptive immune response. In a TLR9-dependent mouse model of sepsis, we found that disease severity was dependent on the timing of sepsis induction, coinciding with the daily changes in TLR9 expression and function. These findings unveil a direct molecular link between the circadian and innate immune systems with important implications for immunoprophylaxis and immunotherapy. PMID:22342842

Rapid Prototyping of Slot Die Devices for Roll to Roll Production of EL Fibers.

PubMed

Bellingham, Alyssa; Bromhead, Nicholas; Fontecchio, Adam

2017-05-29

There is a growing interest in fibers supporting optoelectrical properties for textile and wearable display applications. Solution-processed electroluminescent (EL) material systems can be continuously deposited onto fiber or yarn substrates in a roll-to-roll process, making it easy to scale manufacturing. It is important to have precise control over layer deposition to achieve uniform and reliable light emission from these EL fibers. Slot-die coating offers this control and increases the rate of EL fiber production. Here, we report a highly adaptable, cost-effective 3D printing model for developing slot dies used in automatic coating systems. The resulting slot-die coating system enables rapid, reliable production of alternating current powder-based EL (ACPEL) fibers and can be adapted for many material systems. The benefits of this system over dip-coating for roll-to-roll production of EL fibers are demonstrated in this work.

Hierarchical adaptation scheme for multiagent data fusion and resource management in situation analysis

NASA Astrophysics Data System (ADS)

Benaskeur, Abder R.; Roy, Jean

2001-08-01

Sensor Management (SM) has to do with how to best manage, coordinate and organize the use of sensing resources in a manner that synergistically improves the process of data fusion. Based on the contextual information, SM develops options for collecting further information, allocates and directs the sensors towards the achievement of the mission goals and/or tunes the parameters for the realtime improvement of the effectiveness of the sensing process. Conscious of the important role that SM has to play in modern data fusion systems, we are currently studying advanced SM Concepts that would help increase the survivability of the current Halifax and Iroquois Class ships, as well as their possible future upgrades. For this purpose, a hierarchical scheme has been proposed for data fusion and resource management adaptation, based on the control theory and within the process refinement paradigm of the JDL data fusion model, and taking into account the multi-agent model put forward by the SASS Group for the situation analysis process. The novelty of this work lies in the unified framework that has been defined for tackling the adaptation of both the fusion process and the sensor/weapon management.

Getting Your Sea Legs

PubMed Central

Stoffregen, Thomas A.; Chen, Fu-Chen; Varlet, Manuel; Alcantara, Cristina; Bardy, Benoît G.

2013-01-01

Sea travel mandates changes in the control of the body. The process by which we adapt bodily control to life at sea is known as getting one's sea legs. We conducted the first experimental study of bodily control as maritime novices adapted to motion of a ship at sea. We evaluated postural activity (stance width, stance angle, and the kinematics of body sway) before and during a sea voyage. In addition, we evaluated the role of the visible horizon in the control of body sway. Finally, we related data on postural activity to two subjective experiences that are associated with sea travel; seasickness, and mal de debarquement. Our results revealed rapid changes in postural activity among novices at sea. Before the beginning of the voyage, the temporal dynamics of body sway differed among participants as a function of their (subsequent) severity of seasickness. Body sway measured at sea differed among participants as a function of their (subsequent) experience of mal de debarquement. We discuss implications of these results for general theories of the perception and control of bodily orientation, for the etiology of motion sickness, and for general phenomena of perceptual-motor adaptation and learning. PMID:23840560

Adaptive control applied to Space Station attitude control system

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Clinical effort against secondhand smoke exposure: development of framework and intervention.

PubMed

Winickoff, Jonathan P; Park, Elyse R; Hipple, Bethany J; Berkowitz, Anna; Vieira, Cecilia; Friebely, Joan; Healey, Erica A; Rigotti, Nancy A

2008-08-01

The purpose of this work was to describe a novel process and present results of formative research to develop a pediatric office intervention that uses available systems of care for addressing parental smoking. The scientific development of the intervention occurred in 3 stages. In stage 1, we designed an office system for parental tobacco control in the pediatric outpatient setting on the basis of complementary conceptual frameworks of preventive services delivery, conceptualized for the child health care setting through a process of key interviews with leaders in the field of implementing practice change; existing Public Health Service guidelines that had been shown effective in adult practices; and adaptation of an evidence-based adult office system for tobacco control. This was an iterative process that yielded a theoretically framed intervention prototype. In stage 2, we performed focus-group testing in pediatric practices with pediatricians, nurses, clinical assistants, and key office staff. Using qualitative methods, we adapted the intervention prototype on the basis of this feedback to include 5 key implementation steps for the child health care setting. In stage 3, we presented the intervention to breakout groups at 2 national meetings of pediatric practitioners for additional refinements. The main result was a theoretically grounded intervention that was responsive to the barriers and suggestions raised in the focus groups and at the national meetings. The Clinical Effort Against Secondhand Smoke Exposure intervention was designed to be flexible and adaptable to the particular practices' staffing, resources, and physical configuration. Practice staff can choose materials relevant to their own particular systems of care (www.ceasetobacco.org). Conceptually grounded and focus-group-tested strategies for parental tobacco control are now available for implementation in the pediatric outpatient setting. The tobacco-control intervention-development process might have particular relevance for other chronic pediatric conditions that have a strong evidence base and have available treatments or resources that are underused.

Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Boskovic, Jovan D.

2008-01-01

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

Effect of prism adaptation on left dichotic listening deficit in neglect patients: glasses to hear better?

PubMed

Jacquin-Courtois, S; Rode, G; Pavani, F; O'Shea, J; Giard, M H; Boisson, D; Rossetti, Y

2010-03-01

Unilateral neglect is a disabling syndrome frequently observed following right hemisphere brain damage. Symptoms range from visuo-motor impairments through to deficient visuo-spatial imagery, but impairment can also affect the auditory modality. A short period of adaptation to a rightward prismatic shift of the visual field is known to improve a wide range of hemispatial neglect symptoms, including visuo-manual tasks, mental imagery, postural imbalance, visuo-verbal measures and number bisection. The aim of the present study was to assess whether the beneficial effects of prism adaptation may generalize to auditory manifestations of neglect. Auditory extinction, whose clinical manifestations are independent of the sensory modalities engaged in visuo-manual adaptation, was examined in neglect patients before and after prism adaptation. Two separate groups of neglect patients (all of whom exhibited left auditory extinction) underwent prism adaptation: one group (n = 6) received a classical prism treatment ('Prism' group), the other group (n = 6) was submitted to the same procedure, but wore neutral glasses creating no optical shift (placebo 'Control' group). Auditory extinction was assessed by means of a dichotic listening task performed three times: prior to prism exposure (pre-test), upon prism removal (0 h post-test) and 2 h later (2 h post-test). The total number of correct responses, the lateralization index (detection asymmetry between the two ears) and the number of left-right fusion errors were analysed. Our results demonstrate that prism adaptation can improve left auditory extinction, thus revealing transfer of benefit to a sensory modality that is orthogonal to the visual, proprioceptive and motor modalities directly implicated in the visuo-motor adaptive process. The observed benefit was specific to the detection asymmetry between the two ears and did not affect the total number of responses. This indicates a specific effect of prism adaptation on lateralized processes rather than on general arousal. Our results suggest that the effects of prism adaptation can extend to unexposed sensory systems. The bottom-up approach of visuo-motor adaptation appears to interact with higher order brain functions related to multisensory integration and can have beneficial effects on sensory processing in different modalities. These findings should stimulate the development of therapeutic approaches aimed at bypassing the affected sensory processing modality by adapting other sensory modalities.

A neuro-inspired spike-based PID motor controller for multi-motor robots with low cost FPGAs.

PubMed

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control.

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

PubMed Central

Jimenez-Fernandez, Angel; Jimenez-Moreno, Gabriel; Linares-Barranco, Alejandro; Dominguez-Morales, Manuel J.; Paz-Vicente, Rafael; Civit-Balcells, Anton

2012-01-01

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control. PMID:22666004

The Effect of Locus of Control on School Turnaround

ERIC Educational Resources Information Center

Walston, Bradford

2012-01-01

This research focused on the school turnaround process in six turnaround elementary schools located in urban and rural areas of the state of North Carolina. The purpose of the study was to learn about the challenges facing the six schools, the process of improving student achievement, and, more specifically, the degree to which adaptive leadership…

Epidemic spreading on contact networks with adaptive weights.

PubMed

Zhu, Guanghu; Chen, Guanrong; Xu, Xin-Jian; Fu, Xinchu

2013-01-21

The heterogeneous patterns of interactions within a population are often described by contact networks, but the variety and adaptivity of contact strengths are usually ignored. This paper proposes a modified epidemic SIS model with a birth-death process and nonlinear infectivity on an adaptive and weighted contact network. The links' weights, named as 'adaptive weights', which indicate the intimacy or familiarity between two connected individuals, will reduce as the disease develops. Through mathematical and numerical analyses, conditions are established for population extermination, disease extinction and infection persistence. Particularly, it is found that the fixed weights setting can trigger the epidemic incidence, and that the adaptivity of weights cannot change the epidemic threshold but it can accelerate the disease decay and lower the endemic level. Finally, some corresponding control measures are suggested. Copyright © 2012 Elsevier Ltd. All rights reserved.

Perspectives of construction robots

NASA Astrophysics Data System (ADS)

Stepanov, M. A.; Gridchin, A. M.

2018-03-01

This article is an overview of construction robots features, based on formulating the list of requirements for different types of construction robots in relation to different types of construction works.. It describes a variety of construction works and ways to construct new or to adapt existing robot designs for a construction process. Also, it shows the prospects of AI-controlled machines, implementation of automated control systems and networks on construction sites. In the end, different ways to develop and improve, including ecological aspect, the construction process through the wide robotization, creating of data communication networks and, in perspective, establishing of fully AI-controlled construction complex are formulated.

Locomotor Dysfunction after Long-duration Space Flight and Development of Countermeasures to Facilitate Faster Recovery

NASA Astrophysics Data System (ADS)

Mulavara, Ajitkumar; Wood, Scott; Cohen, Helen; Bloomberg, Jacob

2012-07-01

Exposure to the microgravity conditions of space flight induces adaptive modification in sensorimotor function allowing astronauts to operate in this unique environment. This adaptive state, however, is inappropriate for a 1-g environment. Consequently astronauts must spend time readapting to Earth's gravity following their return to Earth. During this readaptation period, alterations in sensorimotor function cause various disturbances in astronaut gait during postflight walking. They often rely more on vision for postural and gait stability and many report the need for greater cognitive supervision of motor actions that previous to space flight were fully automated. Over the last several years our laboratory has investigated postflight astronaut locomotion with the aim of better understanding how adaptive changes in underlying sensorimotor mechanisms contribute to postflight gait dysfunction. Exposure to the microgravity conditions of space flight induces adaptive modification in the control of vestibularly-mediated reflexive head movement during locomotion after space flight. Furthermore, during motor learning, adaptive transitions are composed of two main mechanisms: strategic and plastic. Strategic mechanisms represent immediate and transitory modifications in control to deal with changes in the prevailing environment that, if prolonged, induce plastic mechanisms designed to automate new behavioral responses. The goal of the present study was to examine the contributions of sensorimotor subsystems such as the vestibular and body load sensing (BLS) somatosensory influences on head movement control during locomotion after long-duration space flight. Further we present data on the two motor learning processes during readaptation of locomotor function after long-duration space flight. Eighteen astronauts performed two tests of locomotion before and after 6 months of space flight: a treadmill walking test to examine vestibular reflexive mechanisms controlling head movement control and a functional mobility test to investigate overall functional locomotor ability. Postflight sessions were given on days 1, 2, 4, 7 after their return. Subjects walked on a treadmill driven at 1.8 m/s while performing a visual task. Motion data from head and trunk segmental motion data were obtained to calculate the angular head pitch (HP) movements during walking trials while subjects performed the visual task, to estimate the contributions of vestibular reflexive mechanisms in HP movements. Astronauts showed a heterogeneous response pattern of both increases and decreases in the amplitude of HP movement. We investigated the underlying mechanisms of this heterogeneity in postflight responses in head movement control by examining data obtained using the same experimental test paradigm on a vestibular clinical population (VC) and in normal subjects undergoing adaptation to acute body load support unloading. Results showed that exposure to unloaded locomotion caused a significant increase in HP movements, whereas in the VC patients the HP movements were significantly decreased. We infer that BLS-mediated somatosensory input centrally modulates vestibular input and can adaptively modify head-movement control during locomotion. Thus, space flight may cause a central adaptation of the converging vestibular and body load-sensing somatosensory systems. To investigate changes in functional mobility astronaut subjects walked at their preferred pace around an obstacle course consisting of several pylons and obstacles set up on a foam floor, which provided an unstable walking surface. Subjects were instructed to walk around the course as fast as possible without touching any of the objects on the course for a total of six individual trials per test session. One of the dependent measures was time to complete the course (TCC, sec). The learning rate over the six trials performed on preflight and the first day after landing (micro curve) was used to characterize the immediate compensatory strategic response. The learning rate over the six trials of the postflight test days (macro curve) was used to characterize the longer-term plastic response. Adaptation to space flight led to a 52% increase in TCC one day after landing. Recovery to pre-flight scores took an average of two weeks after landing. Subjects showed both strategic and plastic recovery patterns based on the slopes obtained from the micro and macro curves compared to preflight. A regression analysis revealed a significant correlation between the slope values of the macro and micro curves indicating a relationship between strategic and plastic recovery processes. Results showed that both strategic and plastic motor learning processes play a role in postflight restoration of functional mobility and showed a dynamic interplay between these two mechanisms during postflight recovery. These results suggest that gait adaptability training programs which are being developed to facilitate adaptive transition to planetary environments, coupled with low levels of electrical stimulation of the vestibular system, can be optimized to engage both strategic and plastic processes to facilitate rapid restoration of postflight functional mobility.

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

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

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

Advances in Adaptive Control Methods

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2009-01-01

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

Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

NASA Technical Reports Server (NTRS)

Kaneshige, John T.; Campbell, Stefan Forrest

2009-01-01

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

Autoresonant control of nonlinear mode in ultrasonic transducer for machining applications.

PubMed

Babitsky, V I; Astashev, V K; Kalashnikov, A N

2004-04-01

Experiments conducted in several countries have shown that the improvement of machining quality can be promoted through conversion of the cutting process into one involving controllable high-frequency vibration at the cutting zone. This is achieved through the generation and maintenance of ultrasonic vibration of the cutting tool to alter the fracture process of work-piece material cutting to one in which loading of the materials at the tool tip is incremental, repetitive and controlled. It was shown that excitation of the high-frequency vibro-impact mode of the tool-workpiece interaction is the most effective way of ultrasonic influence on the dynamic characteristics of machining. The exploitation of this nonlinear mode needs a new method of adaptive control for excitation and stabilisation of ultrasonic vibration known as autoresonance. An approach has been developed to design an autoresonant ultrasonic cutting unit as an oscillating system with an intelligent electronic feedback controlling self-excitation in the entire mechatronic system. The feedback produces the exciting force by means of transformation and amplification of the motion signal. This allows realisation for robust control of fine resonant tuning to bring the nonlinear high Q-factor systems into technological application. The autoresonant control provides the possibility of self-tuning and self-adaptation mechanisms for the system to keep the nonlinear resonant mode of oscillation under unpredictable variation of load, structure and parameters. This allows simple regulation of intensity of the process whilst keeping maximum efficiency at all times. An autoresonant system with supervisory computer control was developed, tested and used for the control of the piezoelectric transducer during ultrasonically assisted cutting. The system has been developed as combined analog-digital, where analog devices process the control signal, and parameters of the devices are controlled digitally by computer. The system was applied for advanced machining of aviation materials.

Adaptive control of a Stewart platform-based manipulator

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Conference Proceedings: Aptitude, Learning, and Instruction. Volume 1. Cognitive Process Analyses of Aptitude,

DTIC Science & Technology

1981-01-01

errors more than twice that shown by the control group (32% versus 13%). The quantitative difference between training and control groups was further...could be enhanced (relative to control groups ) by means of brief training procedures. Educational implications of metaphor research were considered, with...instruction: It addresses itself to the kinds of research and instructional designs required for effective implementation of adaptive instruction ONR

Dual-arm manipulators with adaptive control

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1991-01-01

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

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1995-01-01

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

Optical fiber pressure sensors for adaptive wings

NASA Astrophysics Data System (ADS)

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

1997-06-01

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

Can We Improve Structured Sequence Processing? Exploring the Direct and Indirect Effects of Computerized Training Using a Mediational Model

PubMed Central

Smith, Gretchen N. L.; Conway, Christopher M.; Bauernschmidt, Althea; Pisoni, David B.

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest. PMID:25946222

Can we improve structured sequence processing? Exploring the direct and indirect effects of computerized training using a mediational model.

PubMed

Smith, Gretchen N L; Conway, Christopher M; Bauernschmidt, Althea; Pisoni, David B

2015-01-01

Recent research suggests that language acquisition may rely on domain-general learning abilities, such as structured sequence processing, which is the ability to extract, encode, and represent structured patterns in a temporal sequence. If structured sequence processing supports language, then it may be possible to improve language function by enhancing this foundational learning ability. The goal of the present study was to use a novel computerized training task as a means to better understand the relationship between structured sequence processing and language function. Participants first were assessed on pre-training tasks to provide baseline behavioral measures of structured sequence processing and language abilities. Participants were then quasi-randomly assigned to either a treatment group involving adaptive structured visuospatial sequence training, a treatment group involving adaptive non-structured visuospatial sequence training, or a control group. Following four days of sequence training, all participants were assessed with the same pre-training measures. Overall comparison of the post-training means revealed no group differences. However, in order to examine the potential relations between sequence training, structured sequence processing, and language ability, we used a mediation analysis that showed two competing effects. In the indirect effect, adaptive sequence training with structural regularities had a positive impact on structured sequence processing performance, which in turn had a positive impact on language processing. This finding not only identifies a potential novel intervention to treat language impairments but also may be the first demonstration that structured sequence processing can be improved and that this, in turn, has an impact on language processing. However, in the direct effect, adaptive sequence training with structural regularities had a direct negative impact on language processing. This unexpected finding suggests that adaptive training with structural regularities might potentially interfere with language processing. Taken together, these findings underscore the importance of pursuing designs that promote a better understanding of the mechanisms underlying training-related changes, so that regimens can be developed that help reduce these types of negative effects while simultaneously maximizing the benefits to outcome measures of interest.

Adaptation and colonization history affect the evolution of clines in two introduced species.

PubMed

Keller, Stephen R; Sowell, Dexter R; Neiman, Maurine; Wolfe, Lorne M; Taylor, Douglas R

2009-08-01

Phenotypic and genetic clines have long been synonymous with adaptive evolution. However, other processes (for example, migration, range expansion, invasion) may generate clines in traits or loci across geographical and environmental gradients. It is therefore important to distinguish between clines that represent adaptive evolution and those that result from selectively neutral demographic or genetic processes. We tested for the differentiation of phenotypic traits along environmental gradients using two species in the genus Silene, whilst statistically controlling for colonization history and founder effects. We sampled seed families from across the native and introduced ranges, genotyped individuals and estimated phenotypic differentiation in replicated common gardens. The results suggest that post-glacial expansion of S. vulgaris and S. latifolia involved both neutral and adaptive genetic differentiation (clines) of life history traits along major axes of environmental variation in Europe and North America. Phenotypic clines generally persisted when tested against the neutral expectation, although some clines disappeared (and one cline emerged) when the effects of genetic ancestry were statistically removed. Colonization history, estimated using genetic markers, is a useful null model for tests of adaptive trait divergence, especially during range expansion and invasion when selection and gene flow may not have reached equilibrium.

Activity and adaptation of nitrilotriacetate (NTA)-degrading bacteria: field and laboratory studies

NASA Technical Reports Server (NTRS)

McFeters, G. A.; Egli, T.; Wilberg, E.; Alder, A.; Schneider, R.; Suozzi, M.; Giger, W.

1990-01-01

Adaptation of bacterial activity for the degradation of nitrilotriacetate (NTA) was studied using natural sediment samples and an NTA-degrading bacterium (strain ATCC 29600). Sediment samples from a river with persistent levels of NTA had much higher NTA-degradative activity than comparable samples from a less contaminated control site. When sediment from the control site was exposed to high levels of NTA a 5 day lag preceded an abrupt increase in NTA degradation while strain 29600 colonized on sand and grown in the absence of NTA became induced within eight hours. The induction of strain 29600 was compared between bacteria in suspension and cells attached to sand. The sand-associated bacteria became induced 4 to 5 h before the planktonic suspension and displayed over threefold greater specific activity. Suspensions of strain 29600 became adapted within 8 h when placed in membrane diffusion chambers that were immersed within a municipal wastewater reactor containing NTA. These findings support the concept that induction is a part of the process of bacterial adaptation to degrade NTA and sand-associated bacteria can adapt more quickly to and have a greater degradative activity for NTA than planktonic cells.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

3D Printing Optical Engine for Controlling Material Microstructure

NASA Astrophysics Data System (ADS)

Huang, Wei-Chin; Chang, Kuang-Po; Wu, Ping-Han; Wu, Chih-Hsien; Lin, Ching-Chih; Chuang, Chuan-Sheng; Lin, De-Yau; Liu, Sung-Ho; Horng, Ji-Bin; Tsau, Fang-Hei

Controlling the cooling rate of alloy during melting and resolidification is the most commonly used method for varying the material microstructure and consequently the resuling property. However, the cooling rate of a selective laser melting (SLM) production is restricted by a preset optimal parameter of a good dense product. The head room for locally manipulating material property in a process is marginal. In this study, we invent an Optical Engine for locally controlling material microstructure in a SLM process. It develops an invovative method to control and adjust thermal history of the solidification process to gain desired material microstucture and consequently drastically improving the quality. Process parameters selected locally for specific materials requirement according to designed characteristics by using thermal dynamic principles of solidification process. It utilize a technique of complex laser beam shape of adaptive irradiation profile to permit local control of material characteristics as desired. This technology could be useful for industrial application of medical implant, aerospace and automobile industries.

NASA End-to-End Data System /NEEDS/ information adaptive system - Performing image processing onboard the spacecraft

NASA Technical Reports Server (NTRS)

Kelly, W. L.; Howle, W. M.; Meredith, B. D.

1980-01-01

The Information Adaptive System (IAS) is an element of the NASA End-to-End Data System (NEEDS) Phase II and is focused toward onbaord image processing. Since the IAS is a data preprocessing system which is closely coupled to the sensor system, it serves as a first step in providing a 'Smart' imaging sensor. Some of the functions planned for the IAS include sensor response nonuniformity correction, geometric correction, data set selection, data formatting, packetization, and adaptive system control. The inclusion of these sensor data preprocessing functions onboard the spacecraft will significantly improve the extraction of information from the sensor data in a timely and cost effective manner and provide the opportunity to design sensor systems which can be reconfigured in near real time for optimum performance. The purpose of this paper is to present the preliminary design of the IAS and the plans for its development.

Physical discipline in Chinese American immigrant families: An adaptive culture perspective.

PubMed

Lau, Anna S

2010-07-01

Research on ethnic minority parenting has examined heritage cultural influences and contextual stressors on parenting processes. However, rarely are adaptive cultural processes considered, whereby ethnic minority parents bring their cultural values to bear in adapting to contextual demands in the host society. A survey of 107 Chinese American immigrant parents examined whether use of physical discipline can be predicted by cultural values, contextual stressors, and their interactions. Results indicated that distinct domains of cultural values were related to physical discipline in disparate ways, with some values decreasing risk and others indirectly increasing risk. There was some evidence that cultural values interacted with contextual stress to predict physical discipline. Parent-child acculturation conflicts were only related to physical discipline when parents held strong values about the importance of firm parental control. The findings illustrate how heritage cultural influences and current ecological demands may converge to shape parenting in immigrant families.

Loss of 'complexity' and aging. Potential applications of fractals and chaos theory to senescence

NASA Technical Reports Server (NTRS)

Lipsitz, L. A.; Goldberger, A. L.

1992-01-01

The concept of "complexity," derived from the field of nonlinear dynamics, can be adapted to measure the output of physiologic processes that generate highly variable fluctuations resembling "chaos." We review data suggesting that physiologic aging is associated with a generalized loss of such complexity in the dynamics of healthy organ system function and hypothesize that such loss of complexity leads to an impaired ability to adapt to physiologic stress. This hypothesis is supported by observations showing an age-related loss of complex variability in multiple physiologic processes including cardiovascular control, pulsatile hormone release, and electroencephalographic potentials. If further research supports this hypothesis, measures of complexity based on chaos theory and the related geometric concept of fractals may provide new ways to monitor senescence and test the efficacy of specific interventions to modify the age-related decline in adaptive capacity.

Different levels of learning interact to shape the congruency sequence effect.

PubMed

Weissman, Daniel H; Hawks, Zoë W; Egner, Tobias

2016-04-01

The congruency effect in distracter interference tasks is often reduced after incongruent relative to congruent trials. Moreover, this congruency sequence effect (CSE) is influenced by learning related to concrete stimulus and response features as well as by learning related to abstract cognitive control processes. There is an ongoing debate, however, over whether interactions between these learning processes are best explained by an episodic retrieval account, an adaptation by binding account, or a cognitive efficiency account of the CSE. To make this distinction, we orthogonally manipulated the expression of these learning processes in a novel factorial design involving the prime-probe arrow task. In Experiment 1, these processes interacted in an over-additive fashion to influence CSE magnitude. In Experiment 2, we replicated this interaction while showing it was not driven by conditional differences in the size of the congruency effect. In Experiment 3, we ruled out an alternative account of this interaction as reflecting conditional differences in learning related to concrete stimulus and response features. These findings support an episodic retrieval account of the CSE, in which repeating a stimulus feature from the previous trial facilitates the retrieval and use of previous-trial control parameters, thereby boosting control in the current trial. In contrast, they do not fit with (a) an adaptation by binding account, in which CSE magnitude is directly related to the size of the congruency effect, or (b) a cognitive efficiency account, in which costly control processes are recruited only when behavioral adjustments cannot be mediated by low-level associative mechanisms. (c) 2016 APA, all rights reserved).

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-03-25

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

Catch trials in force field learning influence adaptation and consolidation of human motor memory

PubMed Central

Stockinger, Christian; Focke, Anne; Stein, Thorsten

2014-01-01

Force field studies are a common tool to investigate motor adaptation and consolidation. Thereby, subjects usually adapt their reaching movements to force field perturbations induced by a robotic device. In this context, so-called catch trials, in which the disturbing forces are randomly turned off, are commonly used to detect after-effects of motor adaptation. However, catch trials also produce sudden large motor errors that might influence the motor adaptation and the consolidation process. Yet, the detailed influence of catch trials is far from clear. Thus, the aim of this study was to investigate the influence of catch trials on motor adaptation and consolidation in force field experiments. Therefore, 105 subjects adapted their reaching movements to robot-generated force fields. The test groups adapted their reaching movements to a force field A followed by learning a second interfering force field B before retest of A (ABA). The control groups were not exposed to force field B (AA). To examine the influence of diverse catch trial ratios, subjects received catch trials during force field adaptation with a probability of either 0, 10, 20, 30, or 40%, depending on the group. First, the results on motor adaptation revealed significant differences between the diverse catch trial ratio groups. With increasing amount of catch trials, the subjects' motor performance decreased and subjects' ability to accurately predict the force field—and therefore internal model formation—was impaired. Second, our results revealed that adapting with catch trials can influence the following consolidation process as indicated by a partial reduction to interference. Here, the optimal catch trial ratio was 30%. However, detection of consolidation seems to be biased by the applied measure of performance. PMID:24795598

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Balas, Mark J.

2011-01-01

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

Network models for solving the problem of multicriterial adaptive optimization of investment projects control with several acceptable technologies

NASA Astrophysics Data System (ADS)

Shorikov, A. F.; Butsenko, E. V.

2017-10-01

This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people.

Adaptive Control Allocation in the Presence of Actuator Failures

NASA Technical Reports Server (NTRS)

Liu, Yu; Crespo, Luis G.

2010-01-01

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

Conflict adaptation in emotional task underlies the amplification of target.

PubMed

Chechko, Natalia; Kellermann, Thilo; Schneider, Frank; Habel, Ute

2014-04-01

A primary function of cognitive control is to adjust the cognitive system according to situational demands. The so-called "conflict adaptation effect" elicited in laboratory experiments is supposed to reflect the above function. Neuroimaging studies suggest that adaptation of nonemotional conflict is mediated by the dorsolateral prefrontal cortex through a top-down enhancement of task-relevant (target), relative to task-irrelevant (distractor), stimulus representation in the sensory cortices. The adaptation of emotional conflict, on the other hand, is suggested to be related to the rostral anterior cingulate inhibiting the processing of emotional distractors through a top-down modulation of amygdala responsivity. In the present study, we manipulated, on a trial-by-trial basis, the levels of semantic interference conflict triggered by the incompatibility between emotional faces (targets) and emotional words (distractors) in a modified version of the emotional Stroop task. Similar to previous observations involving nonemotional interference effects, the behavioral adaptation of emotional conflict was found to be paralleled by a stronger recruitment of the fusiform face area. Additional areas related to the conflict adaptation effect were the bilateral insula, the bilateral frontal operculum (fO), the right amygdala, the left precentral and postcentral gyri, and the parietal cortex. These findings suggest that augmentation of cortical responses to task-relevant information in emotional conflict may be related to conflict adaptation processes in a way that has been observed in nonemotional conflict, challenging the view that brain circuitries underlying the conflict adaptation effect depend only on the nature of conflict.

Neural network based adaptive control for nonlinear dynamic regimes

NASA Astrophysics Data System (ADS)

Shin, Yoonghyun

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

Langley Wind Tunnel Data Quality Assurance-Check Standard Results

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Grubb, John P.; Krieger, William B.; Cler, Daniel L.

2000-01-01

A framework for statistical evaluation, control and improvement of wind funnel measurement processes is presented The methodology is adapted from elements of the Measurement Assurance Plans developed by the National Bureau of Standards (now the National Institute of Standards and Technology) for standards and calibration laboratories. The present methodology is based on the notions of statistical quality control (SQC) together with check standard testing and a small number of customer repeat-run sets. The results of check standard and customer repeat-run -sets are analyzed using the statistical control chart-methods of Walter A. Shewhart long familiar to the SQC community. Control chart results are presented for. various measurement processes in five facilities at Langley Research Center. The processes include test section calibration, force and moment measurements with a balance, and instrument calibration.

Model reference adaptive control of robots

NASA Technical Reports Server (NTRS)

Steinvorth, Rodrigo

1991-01-01

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

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

NASA Astrophysics Data System (ADS)

Bai, Jianbo; Li, Yang; Chen, Jianhao

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Implementation of Adaptive Digital Controllers on Programmable Logic Devices

NASA Technical Reports Server (NTRS)

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

2002-01-01

Much has been made of the capabilities of FPGA's (Field Programmable Gate Arrays) in the hardware implementation of fast digital signal processing (DSP) functions. Such capability also makes and FPGA a suitable platform for the digital implementation of closed loop controllers. There are myriad advantages to utilizing an FPGA for discrete-time control functions which include the capability for reconfiguration when SRAM- based FPGA's are employed, fast parallel implementation of multiple control loops and implementations that can meet space level radiation tolerance in a compact form-factor. Other researchers have presented the notion that a second order digital filter with proportional-integral-derivative (PID) control functionality can be implemented in an FPGA. At Marshall Space Flight Center, the Control Electronics Group has been studying adaptive discrete-time control of motor driven actuator systems using digital signal processor (DSF) devices. Our goal is to create a fully digital, flight ready controller design that utilizes an FPGA for implementation of signal conditioning for control feedback signals, generation of commands to the controlled system, and hardware insertion of adaptive control algorithm approaches. While small form factor, commercial DSP devices are now available with event capture, data conversion, pulse width modulated outputs and communication peripherals, these devices are not currently available in designs and packages which meet space level radiation requirements. Meeting our goals requires alternative compact implementation of such functionality to withstand the harsh environment encountered on spacecraft. Radiation tolerant FPGA's are a feasible option for reaching these goals.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: a simulation study.

PubMed

Padhi, Radhakant; Bhardhwaj, Jayender R

2009-06-01

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Responses of crayfish photoreceptor cells following intense light adaptation.

PubMed

Cummins, D R; Goldsmith, T H

1986-01-01

After intense orange adapting exposures that convert 80% of the rhodopsin in the eye to metarhodopsin, rhabdoms become covered with accessory pigment and appear to lose some microvillar order. Only after a delay of hours or even days is the metarhodopsin replaced by rhodopsin (Cronin and Goldsmith 1984). After 24 h of dark adaptation, when there has been little recovery of visual pigment, the photoreceptor cells have normal resting potentials and input resistances, and the reversal potential of the light response is 10-15 mV (inside positive), unchanged from controls. The log V vs log I curve is shifted about 0.6 log units to the right on the energy axis, quantitatively consistent with the decrease in the probability of quantum catch expected from the lowered concentration of rhodopsin in the rhabdoms. Furthermore, at 24 h the photoreceptors exhibit a broader spectral sensitivity than controls, which is also expected from accumulations of metarhodopsin in the rhabdoms. In three other respects, however, the transduction process appears to be light adapted: The voltage responses are more phasic than those of control photoreceptors. The relatively larger effect (compared to controls) of low extracellular Ca++ (1 mmol/l EGTA) in potentiating the photoresponses suggests that the photoreceptors may have elevated levels of free cytoplasmic Ca++. The saturating depolarization is only about 30% as large as the maximal receptor potentials of contralateral, dark controls, and by that measure the log V-log I curve is shifted downward by 0.54 log units.(ABSTRACT TRUNCATED AT 250 WORDS)

Evolutionary online behaviour learning and adaptation in real robots

PubMed Central

Correia, Luís; Christensen, Anders Lyhne

2017-01-01

Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm. PMID:28791130

Long-term dynamics of adaptive evolution in a globally important phytoplankton species to ocean acidification

PubMed Central

Schlüter, Lothar; Lohbeck, Kai T.; Gröger, Joachim P.; Riebesell, Ulf; Reusch, Thorsten B. H.

2016-01-01

Marine phytoplankton may adapt to ocean change, such as acidification or warming, because of their large population sizes and short generation times. Long-term adaptation to novel environments is a dynamic process, and phenotypic change can take place thousands of generations after exposure to novel conditions. We conducted a long-term evolution experiment (4 years = 2100 generations), starting with a single clone of the abundant and widespread coccolithophore Emiliania huxleyi exposed to three different CO2 levels simulating ocean acidification (OA). Growth rates as a proxy for Darwinian fitness increased only moderately under both levels of OA [+3.4% and +4.8%, respectively, at 1100 and 2200 μatm partial pressure of CO2 (Pco2)] relative to control treatments (ambient CO2, 400 μatm). Long-term adaptation to OA was complex, and initial phenotypic responses of ecologically important traits were later reverted. The biogeochemically important trait of calcification, in particular, that had initially been restored within the first year of evolution was later reduced to levels lower than the performance of nonadapted populations under OA. Calcification was not constitutively lost but returned to control treatment levels when high CO2–adapted isolates were transferred back to present-day control CO2 conditions. Selection under elevated CO2 exacerbated a general decrease of cell sizes under long-term laboratory evolution. Our results show that phytoplankton may evolve complex phenotypic plasticity that can affect biogeochemically important traits, such as calcification. Adaptive evolution may play out over longer time scales (>1 year) in an unforeseen way under future ocean conditions that cannot be predicted from initial adaptation responses. PMID:27419227

Action Enhances Acoustic Cues for 3-D Target Localization by Echolocating Bats

PubMed Central

Wohlgemuth, Melville J.

2016-01-01

Under natural conditions, animals encounter a barrage of sensory information from which they must select and interpret biologically relevant signals. Active sensing can facilitate this process by engaging motor systems in the sampling of sensory information. The echolocating bat serves as an excellent model to investigate the coupling between action and sensing because it adaptively controls both the acoustic signals used to probe the environment and movements to receive echoes at the auditory periphery. We report here that the echolocating bat controls the features of its sonar vocalizations in tandem with the positioning of the outer ears to maximize acoustic cues for target detection and localization. The bat’s adaptive control of sonar vocalizations and ear positioning occurs on a millisecond timescale to capture spatial information from arriving echoes, as well as on a longer timescale to track target movement. Our results demonstrate that purposeful control over sonar sound production and reception can serve to improve acoustic cues for localization tasks. This finding also highlights the general importance of movement to sensory processing across animal species. Finally, our discoveries point to important parallels between spatial perception by echolocation and vision. PMID:27608186

Designing for flexible interaction between humans and automation: delegation interfaces for supervisory control.

PubMed

Miller, Christopher A; Parasuraman, Raja

2007-02-01

To develop a method enabling human-like, flexible supervisory control via delegation to automation. Real-time supervisory relationships with automation are rarely as flexible as human task delegation to other humans. Flexibility in human-adaptable automation can provide important benefits, including improved situation awareness, more accurate automation usage, more balanced mental workload, increased user acceptance, and improved overall performance. We review problems with static and adaptive (as opposed to "adaptable") automation; contrast these approaches with human-human task delegation, which can mitigate many of the problems; and revise the concept of a "level of automation" as a pattern of task-based roles and authorizations. We argue that delegation requires a shared hierarchical task model between supervisor and subordinates, used to delegate tasks at various levels, and offer instruction on performing them. A prototype implementation called Playbook is described. On the basis of these analyses, we propose methods for supporting human-machine delegation interactions that parallel human-human delegation in important respects. We develop an architecture for machine-based delegation systems based on the metaphor of a sports team's "playbook." Finally, we describe a prototype implementation of this architecture, with an accompanying user interface and usage scenario, for mission planning for uninhabited air vehicles. Delegation offers a viable method for flexible, multilevel human-automation interaction to enhance system performance while maintaining user workload at a manageable level. Most applications of adaptive automation (aviation, air traffic control, robotics, process control, etc.) are potential avenues for the adaptable, delegation approach we advocate. We present an extended example for uninhabited air vehicle mission planning.

Situating Green Infrastructure in Context: Adaptive Socio-Hydrology for Sustainable Cities - poster

EPA Science Inventory

The benefits of green infrastructure (GI) in controlling urban hydrologic processes have largely focused on practical matters like stormwater management, which drives the planning stage. Green Infrastructure design and implementation usually takes into account physical site chara...

Ecological Principles for Invasive Plant Management

USDA-ARS?s Scientific Manuscript database

Invasive annual grasses continue to advance at an alarming rate despite efforts of control by land managers. Ecologically-based invasive plant management (EBIPM) is a holistic framework that integrates ecosystem health assessment, knowledge of ecological processes and adaptive management into a succ...

Novel Observer Scheme of Fuzzy-MRAS Sensorless Speed Control of Induction Motor Drive

NASA Astrophysics Data System (ADS)

Chekroun, S.; Zerikat, M.; Mechernene, A.; Benharir, N.

2017-01-01

This paper presents a novel approach Fuzzy-MRAS conception for robust accurate tracking of induction motor drive operating in a high-performance drives environment. Of the different methods for sensorless control of induction motor drive the model reference adaptive system (MRAS) finds lot of attention due to its good performance. The analysis of the sensorless vector control system using MRAS is presented and the resistance parameters variations and speed observer using new Fuzzy Self-Tuning adaptive IP Controller is proposed. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The present approach helps to achieve a good dynamic response, disturbance rejection and low to plant parameter variations of the induction motor. In order to verify the performances of the proposed observer and control algorithms and to test behaviour of the controlled system, numerical simulation is achieved. Simulation results are presented and discussed to shown the validity and the performance of the proposed observer.

Meditation-induced cognitive-control states regulate response-conflict adaptation: Evidence from trial-to-trial adjustments in the Simon task.

PubMed

Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Hommel, Bernhard

2015-09-01

Here we consider the possibility that meditation has an immediate impact on information processing. Moreover, we were interested to see whether this impact affects attentional input control, as previous observations suggest, or the handling of response conflict. Healthy adults underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing a Simon task-which assesses conflict-resolution efficiency. While the size of the Simon effect (reflecting the efficiency of handling response conflict) was unaffected by type of meditation, the amount of dynamic behavioral adjustments (i.e., trial-to-trial variability of the Simon effect: the Gratton effect) was considerably smaller after OMM than after FAM. Our findings suggest that engaging in meditation instantly creates a cognitive-control state that has a specific impact on conflict-driven control adaptations. Copyright © 2015 Elsevier Inc. All rights reserved.

Connecting mechanics and bone cell activities in the bone remodeling process: an integrated finite element modeling.

PubMed

Hambli, Ridha

2014-01-01

Bone adaptation occurs as a response to external loadings and involves bone resorption by osteoclasts followed by the formation of new bone by osteoblasts. It is directly triggered by the transduction phase by osteocytes embedded within the bone matrix. The bone remodeling process is governed by the interactions between osteoblasts and osteoclasts through the expression of several autocrine and paracrine factors that control bone cell populations and their relative rate of differentiation and proliferation. A review of the literature shows that despite the progress in bone remodeling simulation using the finite element (FE) method, there is still a lack of predictive models that explicitly consider the interaction between osteoblasts and osteoclasts combined with the mechanical response of bone. The current study attempts to develop an FE model to describe the bone remodeling process, taking into consideration the activities of osteoclasts and osteoblasts. The mechanical behavior of bone is described by taking into account the bone material fatigue damage accumulation and mineralization. A coupled strain-damage stimulus function is proposed, which controls the level of autocrine and paracrine factors. The cellular behavior is based on Komarova et al.'s (2003) dynamic law, which describes the autocrine and paracrine interactions between osteoblasts and osteoclasts and computes cell population dynamics and changes in bone mass at a discrete site of bone remodeling. Therefore, when an external mechanical stress is applied, bone formation and resorption is governed by cells dynamic rather than adaptive elasticity approaches. The proposed FE model has been implemented in the FE code Abaqus (UMAT routine). An example of human proximal femur is investigated using the model developed. The model was able to predict final human proximal femur adaptation similar to the patterns observed in a human proximal femur. The results obtained reveal complex spatio-temporal bone adaptation. The proposed FEM model gives insight into how bone cells adapt their architecture to the mechanical and biological environment.

The insula: a critical neural substrate for craving and drug seeking under conflict and risk

PubMed Central

Naqvi, Nasir H.; Gaznick, Natassia; Tranel, Daniel; Bechara, Antoine

2014-01-01

Drug addiction is characterized by the inability to control drug use when it results in negative consequences or conflicts with more adaptive goals. Our previous work showed that damage to the insula disrupted addiction to cigarette smoking—the first time that the insula was shown to be a critical neural substrate for addiction. Here, we review those findings, as well as more recent studies that corroborate and extend them, demonstrating the role of the insula in (1) incentive motivational processes that drive addictive behavior, (2) control processes that moderate or inhibit addictive behavior, and (3) interoceptive processes that represent bodily states associated with drug use. We then describe a theoretical framework that attempts to integrate these seemingly disparate findings. In this framework, the insula functions in the recall of interoceptive drug effects during craving and drug seeking under specific conditions where drug taking is perceived as risky and/or where there is conflict between drug taking and more adaptive goals. We describe this framework in an evolutionary context and discuss its implications for understanding the mechanisms of behavior change in addiction treatments. PMID:24690001

Unity with PMA-2 attached awaits further processing in the SSPF

NASA Technical Reports Server (NTRS)

1998-01-01

The International Space Station's (ISS) Unity node, with Pressurized Mating Adapter (PMA)-2 attached, awaits further processing by Boeing technicians in its workstand in the Space Station Processing Facility (SSPF). The Unity node is the first element of the ISS to be manufactured in the United States and is currently scheduled to lift off aboard the Space Shuttle Endeavour on STS-88 later this year. Unity has two PMAs attached to it now that this mate is completed. PMAs are conical docking adapters which will allow the docking systems used by the Space Shuttle and by Russian modules to attach to the node's hatches and berthing mechanisms. Once in orbit, Unity, which has six hatches, will be mated with the already orbiting Control Module and will eventually provide attachment points for the U.S. laboratory module; Node 3; an early exterior framework or truss for the station; an airlock; and a multi-windowed cupola. The Control Module, or Functional Cargo Block, is a U.S.-funded and Russian-built component that will be launched aboard a Russian rocket from Kazakstan.

Unity with PMA-2 attached awaits further processing in the SSPF

NASA Technical Reports Server (NTRS)

1998-01-01

The International Space Station's (ISS) Unity node, with Pressurized Mating Adapter (PMA)-2 attached, awaits further processing in the Space Station Processing Facility (SSPF). The Unity node is the first element of the ISS to be manufactured in the United States and is currently scheduled to lift off aboard the Space Shuttle Endeavour on STS-88 later this year. Unity has two PMAs attached to it now that this mate is completed. PMAs are conical docking adapters which will allow the docking systems used by the Space Shuttle and by Russian modules to attach to the node's hatches and berthing mechanisms. Once in orbit, Unity, which has six hatches, will be mated with the already orbiting Control Module and will eventually provide attachment points for the U.S. laboratory module; Node 3; an early exterior framework or truss for the station; an airlock; and a multi-windowed cupola. The Control Module, or Functional Cargo Block, is a U.S.- funded and Russian-built component that will be launched aboard a Russian rocket from Kazakstan.

Robust adaptive vibration control of a flexible structure.

PubMed

Khoshnood, A M; Moradi, H M

2014-07-01

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

Structure Learning in Bayesian Sensorimotor Integration

PubMed Central

Genewein, Tim; Hez, Eduard; Razzaghpanah, Zeynab; Braun, Daniel A.

2015-01-01

Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration. PMID:26305797

The Complex Nature of Bilinguals' Language Usage Modulates Task-Switching Outcomes

PubMed Central

Yang, Hwajin; Hartanto, Andree; Yang, Sujin

2016-01-01

In view of inconsistent findings regarding bilingual advantages in executive functions (EF), we reviewed the literature to determine whether bilinguals' different language usage causes measureable changes in the shifting aspects of EF. By drawing on the theoretical framework of the adaptive control hypothesis—which postulates a critical link between bilinguals' varying demands on language control and adaptive cognitive control (Green and Abutalebi, 2013), we examined three factors that characterize bilinguals' language-switching experience: (a) the interactional context of conversational exchanges, (b) frequency of language switching, and (c) typology of code-switching. We also examined whether methodological variations in previous task-switching studies modulate task-specific demands on control processing and lead to inconsistencies in the literature. Our review demonstrates that not only methodological rigor but also a more finely grained, theory-based approach will be required to understand the cognitive consequences of bilinguals' varied linguistic practices in shifting EF. PMID:27199800

Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience

NASA Astrophysics Data System (ADS)

Billard, Aude

2000-10-01

This paper summarizes a number of experiments in biologically inspired robotics. The common feature to all experiments is the use of artificial neural networks as the building blocks for the controllers. The experiments speak in favor of using a connectionist approach for designing adaptive and flexible robot controllers, and for modeling neurological processes. I present 1) DRAMA, a novel connectionist architecture, which has general property for learning time series and extracting spatio-temporal regularities in multi-modal and highly noisy data; 2) Robota, a doll-shaped robot, which imitates and learns a proto-language; 3) an experiment in collective robotics, where a group of 4 to 15 Khepera robots learn dynamically the topography of an environment whose features change frequently; 4) an abstract, computational model of primate ability to learn by imitation; 5) a model for the control of locomotor gaits in a quadruped legged robot.

Right ventrolateral prefrontal cortex mediates individual differences in conflict-driven cognitive control

PubMed Central

Egner, Tobias

2013-01-01

Conflict adaptation – a conflict-triggered improvement in the resolution of conflicting stimulus or response representations – has become a widely used probe of cognitive control processes in both healthy and clinical populations. Previous functional magnetic resonance imaging (fMRI) studies have localized activation foci associated with conflict resolution to dorsolateral prefrontal cortex (dlPFC). The traditional group-analysis approach employed in these studies highlights regions that are, on average, activated during conflict resolution, but does not necessarily reveal areas mediating individual differences in conflict resolution, because between-subject variance is treated as noise. Here, we employed a complementary approach in order to elucidate the neural bases of variability in the proficiency of conflict-driven cognitive control. We analyzed two independent fMRI data sets of face-word Stroop tasks by using individual variability in the behavioral expression of conflict adaptation as the metric against which brain activation was regressed, while controlling for individual differences in mean reaction time and Stroop interference. Across the two experiments, a replicable neural substrate of individual variation in conflict adaptation was found in ventrolateral prefrontal cortex (vlPFC), specifically, in the right inferior frontal gyrus, pars orbitalis (BA 47). Unbiased regression estimates showed that variability in activity in this region accounted for ~40% of the variance in behavioral expression of conflict adaptation across subjects, thus documenting a heretofore unsuspected key role for vlPFC in mediating conflict-driven adjustments in cognitive control. We speculate that vlPFC plays a primary role in conflict control that is supplemented by dlPFC recruitment under conditions of suboptimal performance. PMID:21568631

Right ventrolateral prefrontal cortex mediates individual differences in conflict-driven cognitive control.

PubMed

Egner, Tobias

2011-12-01

Conflict adaptation--a conflict-triggered improvement in the resolution of conflicting stimulus or response representations--has become a widely used probe of cognitive control processes in both healthy and clinical populations. Previous fMRI studies have localized activation foci associated with conflict resolution to dorsolateral PFC (dlPFC). The traditional group analysis approach employed in these studies highlights regions that are, on average, activated during conflict resolution, but does not necessarily reveal areas mediating individual differences in conflict resolution, because between-subject variance is treated as noise. Here, we employed a complementary approach to elucidate the neural bases of variability in the proficiency of conflict-driven cognitive control. We analyzed two independent fMRI data sets of face-word Stroop tasks by using individual variability in the behavioral expression of conflict adaptation as the metric against which brain activation was regressed while controlling for individual differences in mean RT and Stroop interference. Across the two experiments, a replicable neural substrate of individual variation in conflict adaptation was found in ventrolateral PFC (vlPFC), specifically, in the right inferior frontal gyrus, pars orbitalis (BA 47). Unbiased regression estimates showed that variability in activity in this region accounted for ∼ 40% of the variance in behavioral expression of conflict adaptation across subjects, thus documenting a heretofore unsuspected key role for vlPFC in mediating conflict-driven adjustments in cognitive control. We speculate that vlPFC plays a primary role in conflict control that is supplemented by dlPFC recruitment under conditions of suboptimal performance.

Information-educational environment with adaptive control of learning process

NASA Astrophysics Data System (ADS)

Modjaev, A. D.; Leonova, N. M.

2017-01-01

Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.

Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems.

PubMed

Wang, Cong; Wang, Min; Liu, Tengfei; Hill, David J

2012-10-01

This paper studies learning from adaptive neural control (ANC) for a class of nonlinear strict-feedback systems with unknown affine terms. To achieve the purpose of learning, a simple input-to-state stability (ISS) modular ANC method is first presented to ensure the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in finite time. Subsequently, it is proven that learning with the proposed stable ISS-modular ANC can be achieved. The cascade structure and unknown affine terms of the considered systems make it very difficult to achieve learning using existing methods. To overcome these difficulties, the stable closed-loop system in the control process is decomposed into a series of linear time-varying (LTV) perturbed subsystems with the appropriate state transformation. Using a recursive design, the partial persistent excitation condition for the radial basis function neural network (NN) is established, which guarantees exponential stability of LTV perturbed subsystems. Consequently, accurate approximation of the closed-loop system dynamics is achieved in a local region along recurrent orbits of closed-loop signals, and learning is implemented during a closed-loop feedback control process. The learned knowledge is reused to achieve stability and an improved performance, thereby avoiding the tremendous repeated training process of NNs. Simulation studies are given to demonstrate the effectiveness of the proposed method.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Using virtual reality to augment perception, enhance sensorimotor adaptation, and change our minds.

PubMed

Wright, W Geoffrey

2014-01-01

Technological advances that involve human sensorimotor processes can have both intended and unintended effects on the central nervous system (CNS). This mini review focuses on the use of virtual environments (VE) to augment brain functions by enhancing perception, eliciting automatic motor behavior, and inducing sensorimotor adaptation. VE technology is becoming increasingly prevalent in medical rehabilitation, training simulators, gaming, and entertainment. Although these VE applications have often been shown to optimize outcomes, whether it be to speed recovery, reduce training time, or enhance immersion and enjoyment, there are inherent drawbacks to environments that can potentially change sensorimotor calibration. Across numerous VE studies over the years, we have investigated the effects of combining visual and physical motion on perception, motor control, and adaptation. Recent results from our research involving exposure to dynamic passive motion within a visually-depicted VE reveal that short-term exposure to augmented sensorimotor discordance can result in systematic aftereffects that last beyond the exposure period. Whether these adaptations are advantageous or not, remains to be seen. Benefits as well as risks of using VE-driven sensorimotor stimulation to enhance brain processes will be discussed.

Certification Considerations for Adaptive Systems

NASA Technical Reports Server (NTRS)

Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

2015-01-01

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Adaptive Process Controls and Ultrasonics for High Temperature PEM MEA Manufacture

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

Walczyk, Daniel F.

2015-08-26

The purpose of this 5-year DOE-sponsored project was to address major process bottlenecks associated with fuel cell manufacturing. New technologies were developed to significantly reduce pressing cycle time for high temperature PEM membrane electrode assembly (MEA) through the use of novel, robust ultrasonic (U/S) bonding processes along with low temperature (<100°C) PEM MEAs. In addition, greater manufacturing uniformity and performance was achieved through (a) an investigation into the causes of excessive variation in ultrasonically and thermally bonded MEAs using more diagnostics applied during the entire fabrication and cell build process, and (b) development of rapid, yet simple quality control measurementmore » techniques for use by industry.« less

Evolutionary grinding model for nanometric control of surface roughness for aspheric optical surfaces.

PubMed

Han, Jeong-Yeol; Kim, Sug-Whan; Han, Inwoo; Kim, Geon-Hee

2008-03-17

A new evolutionary grinding process model has been developed for nanometric control of material removal from an aspheric surface of Zerodur substrate. The model incorporates novel control features such as i) a growing database; ii) an evolving, multi-variable regression equation; and iii) an adaptive correction factor for target surface roughness (Ra) for the next machine run. This process model demonstrated a unique evolutionary controllability of machining performance resulting in the final grinding accuracy (i.e. averaged difference between target and measured surface roughness) of -0.2+/-2.3(sigma) nm Ra over seven trial machine runs for the target surface roughness ranging from 115 nm to 64 nm Ra.

Treatment of the control mechanisms of light airplanes in the flutter clearance process

NASA Technical Reports Server (NTRS)

Breitbach, E. J.

1979-01-01

It has become more and more evident that many difficulties encountered in the course of aircraft flutter analyses can be traced to strong localized nonlinearities in the control mechanisms. To cope with these problems, more reliable mathematical models paying special attention to control system nonlinearities were established by means of modified ground vibration test procedures in combination with suitably adapted modal synthesis approaches. Three different concepts are presented.

Soft Sensors: Chemoinformatic Model for Efficient Control and Operation in Chemical Plants.

PubMed

Funatsu, Kimito

2016-12-01

Soft sensor is statistical model as an essential tool for controlling pharmaceutical, chemical and industrial plants. I introduce soft sensor, the roles, the applications, the problems and the research examples such as adaptive soft sensor, database monitoring and efficient process control. The use of soft sensor enables chemical industrial plants to be operated more effectively and stably. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

Tryfonidis, Michail

It has been observed that during orbital spaceflight the absence of gravitation related sensory inputs causes incongruence between the expected and the actual sensory feedback resulting from voluntary movements. This incongruence results in a reinterpretation or neglect of gravity-induced sensory input signals. Over time, new internal models develop, gradually compensating for the loss of spatial reference. The study of adaptation of goal-directed movements is the main focus of this thesis. The hypothesis is that during the adaptive learning process the neural connections behave in ways that can be described by an adaptive control method. The investigation presented in this thesis includes two different sets of experiments. A series of dart throwing experiments took place onboard the space station Mir. Experiments also took place at the Biomechanics lab at MIT, where the subjects performed a series of continuous trajectory tracking movements while a planar robotic manipulandum exerted external torques on the subjects' moving arms. The experimental hypothesis for both experiments is that during the first few trials the subjects will perform poorly trying to follow a prescribed trajectory, or trying to hit a target. A theoretical framework is developed that is a modification of the sliding control method used in robotics. The new control framework is an attempt to explain the adaptive behavior of the subjects. Numerical simulations of the proposed framework are compared with experimental results and predictions from competitive models. The proposed control methodology extends the results of the sliding mode theory to human motor control. The resulting adaptive control model of the motor system is robust to external dynamics, even those of negative gain, uses only position and velocity feedback, and achieves bounded steady-state error without explicit knowledge of the system's nonlinearities. In addition, the experimental and modeling results demonstrate that visuomotor learning is important not only for error correction through internal model adaptation on ground or in microgravity, but also for the minimization of the total mean-square error in the presence of random variability. Thus human intelligent decision displays certain attributes that seem to conform to Bayesian statistical games. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)

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

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

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

Adaptive neural network motion control for aircraft under uncertainty conditions

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort Modifications

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.

Sensorimotor adaptation of point-to-point arm movements after spaceflight: the role of internal representation of gravity force in trajectory planning.

PubMed

Gaveau, Jérémie; Paizis, Christos; Berret, Bastien; Pozzo, Thierry; Papaxanthis, Charalambos

2011-08-01

After an exposure to weightlessness, the central nervous system operates under new dynamic and sensory contexts. To find optimal solutions for rapid adaptation, cosmonauts have to decide whether parameters from the world or their body have changed and to estimate their properties. Here, we investigated sensorimotor adaptation after a spaceflight of 10 days. Five cosmonauts performed forward point-to-point arm movements in the sagittal plane 40 days before and 24 and 72 h after the spaceflight. We found that, whereas the shape of hand velocity profiles remained unaffected after the spaceflight, hand path curvature significantly increased 1 day after landing and returned to the preflight level on the third day. Control experiments, carried out by 10 subjects under normal gravity conditions, showed that loading the arm with varying loads (from 0.3 to 1.350 kg) did not affect path curvature. Therefore, changes in path curvature after spaceflight cannot be the outcome of a control process based on the subjective feeling that arm inertia was increased. By performing optimal control simulations, we found that arm kinematics after exposure to microgravity corresponded to a planning process that overestimated the gravity level and optimized movements in a hypergravity environment (∼1.4 g). With time and practice, the sensorimotor system was recalibrated to Earth's gravity conditions, and cosmonauts progressively generated accurate estimations of the body state, gravity level, and sensory consequences of the motor commands (72 h). These observations provide novel insights into how the central nervous system evaluates body (inertia) and environmental (gravity) states during sensorimotor adaptation of point-to-point arm movements after an exposure to weightlessness.

Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

NASA Technical Reports Server (NTRS)

Grace, Joseph M.; Verseux, Cyprien; Gentry, Diana; Moffet, Amy; Thayabaran, Ramanen; Wong, Nathan; Rothschild, Lynn

2013-01-01

The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the number or growth rate of surviving cells. We are on our second prototype iteration, with demonstrated functions of microbial growth monitoring and dynamic exposure to UV-C radiation and temperature. We plan to add functionality for general chemical presence or absence by Nov. 2013. By making the project low-cost and open-source, we hope to encourage others to use it as a basis for future development of a common microbial environmental adaptation testbed.

Adaptation of community health worker-delivered behavioral activation for torture survivors in Kurdistan, Iraq.

PubMed

Magidson, J F; Lejuez, C W; Kamal, T; Blevins, E J; Murray, L K; Bass, J K; Bolton, P; Pagoto, S

2015-12-01

Growing evidence supports the use of Western therapies for the treatment of depression, trauma, and stress delivered by community health workers (CHWs) in conflict-affected, resource-limited countries. A recent randomized controlled trial (Bolton et al . 2014 a ) supported the efficacy of two CHW-delivered interventions, cognitive processing therapy (CPT) and brief behavioral activation treatment for depression (BATD), for reducing depressive symptoms and functional impairment among torture survivors in the Kurdish region of Iraq. This study describes the adaptation of the CHW-delivered BATD approach delivered in this trial (Bolton et al .2014 a ), informed by the Assessment-Decision-Administration-Production-Topical experts-Integration-Training-Testing (ADAPT-ITT) framework for intervention adaptation (Wingood & DiClemente, 2008). Cultural modifications, adaptations for low-literacy, and tailored training and supervision for non-specialist CHWs are presented, along with two clinical case examples to illustrate delivery of the adapted intervention in this setting. Eleven CHWs, a study psychiatrist, and the CHW clinical supervisor were trained in BATD. The adaptation process followed the ADAPT-ITT framework and was iterative with significant input from the on-site supervisor and CHWs. Modifications were made to fit Kurdish culture, including culturally relevant analogies, use of stickers for behavior monitoring, cultural modifications to behavioral contracts, and including telephone-delivered sessions to enhance feasibility. BATD was delivered by CHWs in a resource-poor, conflict-affected area in Kurdistan, Iraq, with some important modifications, including low-literacy adaptations, increased cultural relevancy of clinical materials, and tailored training and supervision for CHWs. Barriers to implementation, lessons learned, and recommendations for future efforts to adapt behavioral therapies for resource-limited, conflict-affected areas are discussed.

Adaptive powertrain control for plugin hybrid electric vehicles

DOEpatents

Kedar-Dongarkar, Gurunath; Weslati, Feisel

2013-10-15

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Apparatus and Method for Assessing Vestibulo-Ocular Function

NASA Technical Reports Server (NTRS)

Shelhamer, Mark J. (Inventor)

2015-01-01

A system for assessing vestibulo-ocular function includes a motion sensor system adapted to be coupled to a user's head; a data processing system configured to communicate with the motion sensor system to receive the head-motion signals; a visual display system configured to communicate with the data processing system to receive image signals from the data processing system; and a gain control device arranged to be operated by the user and to communicate gain adjustment signals to the data processing system.

'I was in control of it from the start': A qualitative study of men's experiences of positive adjustment following a heart attack.

PubMed

Smith, Fran; Banwell, Elizabeth; Rakhit, Roby

2017-09-01

A qualitative design was used to explore the experience of positive adjustment following a heart attack. Ten men attending a cardiac rehabilitation programme completed in-depth semi-structured interviews. An overarching theme: 'I was in control of it from the start' emerged with six subthemes, relating to intrapersonal and interpersonal factors and processes. The subthemes reflected the importance of identifying controllable versus non-controllable factors and employing adaptive coping strategies.

KSC-98pc151

NASA Image and Video Library

1998-01-14

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

Active chatter suppression with displacement-only measurement in turning process

NASA Astrophysics Data System (ADS)

Ma, Haifeng; Wu, Jianhua; Yang, Liuqing; Xiong, Zhenhua

2017-08-01

Regenerative chatter is a major hindrance for achieving high quality and high production rate in machining processes. Various active controllers have been proposed to mitigate chatter. However, most of existing controllers were developed on the basis of multi-states feedback of the system and state observers were usually needed. Moreover, model parameters of the machining process (mass, damping and stiffness) were required in existing active controllers. In this study, an active sliding mode controller, which employs a dynamic output feedback sliding surface for the unmatched condition and an adaptive law for disturbance estimation, is designed, analyzed, and validated for chatter suppression in turning process. Only displacement measurement is required by this approach. Other sensors and state observers are not needed. Moreover, it facilitates a rapid implementation since the designed controller is established without using model parameters of the turning process. Theoretical analysis, numerical simulations and experiments on a computer numerical control (CNC) lathe are presented. It shows that the chatter can be substantially attenuated and the chatter-free region can be significantly expanded with the presented method.

Research environments that promote integrity.

PubMed

Jeffers, Brenda Recchia; Whittemore, Robin

2005-01-01

The body of empirical knowledge about research integrity and the factors that promote research integrity in nursing research environments remains small. To propose an internal control model as an innovative framework for the design and structure of nursing research environments that promote integrity. An internal control model is adapted to illustrate its use for conceptualizing and designing research environments that promote integrity. The internal control model integrates both the organizational elements necessary to promote research integrity and the processes needed to assess research environments. The model provides five interrelated process components within which any number of research integrity variables and processes may be used and studied: internal control environment, risk assessment, internal control activities, monitoring, and information and communication. The components of the proposed research integrity internal control model proposed comprise an integrated conceptualization of the processes that provide reasonable assurance that research integrity will be promoted within the nursing research environment. Schools of nursing can use the model to design, implement, and evaluate systems that promote research integrity. The model process components need further exploration to substantiate the use of the model in nursing research environments.

Analysis and Characterization of 3-(3,4-Dichlorophenyl)-1,1-Dimethylurea (DCMU)-resistant Euglena

PubMed Central

Calvayrac, Régis; Bomsel, Jean-Loup; Laval-Martin, Danielle

1979-01-01

Cultures of Euglena gracilis Klebs strain Z Pringsheim were grown photoorganotrophically in the presence of different concentrations of 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) in the range of 0.05 to 250 micromolar. Cultures were serially transferred and various metabolic parameters were followed for 10 weeks. A process of adaptation occurred which was divided operationally into three phases. A phase of ultrastructural disorganization occurred, succeeded by a recovery phase; their intensity and duration were functions of the dose of DCMU. A stable adaptation phase then ensued. This phase was observed in all cultures except that exposed to the highest DCMU concentration. Adapted cells from all of the DCMU cultures contained twice the protein and half the paramylon of the control cells and thus utilized the carbon source to accumulate cellular reserves with only half the efficiency of controls. DCMU affected cellular metabolism as well as photosynthesis. The energy charge remained at high levels throughout adaptation, although the size of the adenylate pool was half that of controls at the disorganized phase. At this stage the ultrastructure of chloroplasts and mitochondria was considerably modified. The progressive changes of the parameters studied appeared to affect all of the cells in a given culture. Images PMID:16660827

Transcutaneous vagus nerve stimulation (tVNS) enhances conflict-triggered adjustment of cognitive control.

PubMed

Fischer, Rico; Ventura-Bort, Carlos; Hamm, Alfons; Weymar, Mathias

2018-04-24

Response conflicts play a prominent role in the flexible adaptation of behavior as they represent context-signals that indicate the necessity for the recruitment of cognitive control. Previous studies have highlighted the functional roles of the affectively aversive and arousing quality of the conflict signal in triggering the adaptation process. To further test this potential link with arousal, participants performed a response conflict task in two separate sessions with either transcutaneous vagus nerve stimulation (tVNS), which is assumed to activate the locus coeruleus-noradrenaline (LC-NE) system, or with neutral sham stimulation. In both sessions the N2 and P3 event-related potentials (ERP) were assessed. In line with previous findings, conflict interference, the N2 and P3 amplitude were reduced after conflict. Most importantly, this adaptation to conflict was enhanced under tVNS compared to sham stimulation for conflict interference and the N2 amplitude. No effect of tVNS on the P3 component was found. These findings suggest that tVNS increases behavioral and electrophysiological markers of adaptation to conflict. Results are discussed in the context of the potentially underlying LC-NE and other neuromodulatory (e.g., GABA) systems. The present findings add important pieces to the understanding of the neurophysiological mechanisms of conflict-triggered adjustment of cognitive control.

Temporal dynamics of contrast gain in single cells of the cat striate cortex.

PubMed

Bonds, A B

1991-03-01

The response amplitude of cat striate cortical cells is usually reduced after exposure to high-contrast stimuli. The temporal characteristics and contrast sensitivity of this phenomenon were explored by stimulating cortical cells with drifting gratings in which contrast sequentially incremented and decremented in stepwise fashion over time. All responses showed a clear hysteresis, in which contrast gain dropped on average 0.36 log unit and then returned to baseline values within 60 s. Noticeable gain adjustments were seen in as little as 3 s and with peak contrasts as low as 3%. Contrast adaptation was absent in responses from LGN cells. Adaptation was found to depend on temporal frequency of stimulation, with greater and more rapid adaptation at higher temporal frequencies. Two different tests showed that the mechanism controlling response reduction was influenced primarily by stimulus contrast rather than response amplitude. These results support the existence of a rapid and sensitive cortically based system that normalizes the output of cortical cells as a function of local mean contrast. Control of the adaptation appears to arise at least in part across a population of cells, which is consistent with the idea that the gain control serves to limit the information converging from many cells onto subsequent processing areas.

Translation and cultural adaptation of a specific instrument for measuring asthma control and asthma status: the Asthma Control and Communication Instrument

PubMed Central

Tavares, Michelle Gonçalves de Souza; Brümmer, Carolina Finardi; Nicolau, Gabriela Valente; de Melo, José Tavares; Nazário, Nazaré Otilia; Steidle, Leila John Marques; Patino, Cecília Maria; Pizzichini, Marcia Margaret Menezes; Pizzichini, Emílio

2017-01-01

ABSTRACT Objective: To translate the Asthma Control and Communication Instrument (ACCI) to Portuguese and adapt it for use in Brazil. Methods: The ACCI was translated to Portuguese and adapted for use in Brazil in accordance with internationally accepted guidelines. The protocol included the following steps: permission and rights of use granted by the original author; translation of the ACCI from English to Portuguese; reconciliation; back-translation; review and harmonization of the back-translation; approval from the original author; review of the Portuguese version of the ACCI by an expert panel; cognitive debriefing (the clarity, understandability, and acceptability of the translated version being tested in a sample of the target population); and reconciliation and preparation of the final version. Results: During the cognitive debriefing process, 41 asthma patients meeting the inclusion criteria completed the ACCI and evaluated the clarity of the questions/statements. The clarity index for all ACCI items was > 0.9, meaning that all items were considered to be clear. Conclusions: The ACCI was successfully translated to Portuguese and culturally adapted for use in Brazil, the translated version maintaining the psychometric properties of the original version. The ACCI can be used in clinical practice because it is easy to understand and easily applied. PMID:29365000

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

NASA Astrophysics Data System (ADS)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.