Expressing Adaptation Strategies Using Adaptation Patterns

ERIC Educational Resources Information Center

Zemirline, N.; Bourda, Y.; Reynaud, C.

2012-01-01

Today, there is a real challenge to enable personalized access to information. Several systems have been proposed to address this challenge including Adaptive Hypermedia Systems (AHSs). However, the specification of adaptation strategies remains a difficult task for creators of such systems. In this paper, we consider the problem of the definition…

Adaptive control strategies for flexible robotic arm

NASA Technical Reports Server (NTRS)

Bialasiewicz, Jan T.

1993-01-01

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

Dual-thread parallel control strategy for ophthalmic adaptive optics.

PubMed

Yu, Yongxin; Zhang, Yuhua

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

Dual-thread parallel control strategy for ophthalmic adaptive optics

PubMed Central

Yu, Yongxin; Zhang, Yuhua

2015-01-01

To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a closed loop updating frequency up to 110 Hz, and demonstrated robust compensation for ocular wave aberration up to 50 Hz in an adaptive optics scanning laser ophthalmoscope. PMID:25866498

Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

NASA Astrophysics Data System (ADS)

Ji, Xuewu; He, Xiangkun; Lv, Chen; Liu, Yahui; Wu, Jian

2018-06-01

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.

Comparison of Strategies for Climate Change Adaptation of Water Supply and Flood Control Reservoirs

NASA Astrophysics Data System (ADS)

Ng, T. L.; Yang, P.; Bhushan, R.

2016-12-01

With climate change, streamflows are expected to become more fluctuating, with more frequent and intense floods and droughts. This complicates reservoir operation, which is highly sensitive to inflow variability. We make a comparative evaluation of three strategies for adapting reservoirs to climate-induced shifts in streamflow patterns. Specifically, we examine the effectiveness of (i) expanding the capacities of reservoirs by way of new off-stream reservoirs, (ii) introducing wastewater reclamation to augment supplies, and (iii) improving real-time streamflow forecasts for more optimal decision-making. The first two are hard strategies involving major infrastructure modifications, while the third a soft strategy entailing adjusting the system operation. A comprehensive side-by-side comparison of the three strategies is as yet lacking in the literature despite the many past studies investigating the strategies individually. To this end, we developed an adaptive forward-looking linear program that solves to yield the optimal decisions for the current time as a function of an ensemble forecast of future streamflows. Solving the model repeatedly on a rolling basis with regular updating of the streamflow forecast simulates the system behavior over the entire operating horizon. Results are generated for two hypothetical water supply and flood control reservoirs of differing inflows and demands. Preliminary findings suggest that of the three strategies, improving streamflow forecasts to be most effective in mitigating the effects of climate change. We also found that, in average terms, both additional reservoir capacity and wastewater reclamation have potential to reduce water shortage and downstream flooding. However, in the worst case, the potential of the former to reduce water shortage is limited, and similarly so the potential of the latter to reduce downstream flooding.

Robust adaptive vibration control of a flexible structure.

PubMed

Khoshnood, A M; Moradi, H M

2014-07-01

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

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

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.

Distinct motor strategies underlying split-belt adaptation in human walking and running.

PubMed

Ogawa, Tetsuya; Kawashima, Noritaka; Obata, Hiroki; Kanosue, Kazuyuki; Nakazawa, Kimitaka

2015-01-01

The aim of the present study was to elucidate the adaptive and de-adaptive nature of human running on a split-belt treadmill. The degree of adaptation and de-adaptation was compared with those in walking by calculating the antero-posterior component of the ground reaction force (GRF). Adaptation to walking and running on a split-belt resulted in a prominent asymmetry in the movement pattern upon return to the normal belt condition, while the two components of the GRF showed different behaviors depending on the gaits. The anterior braking component showed prominent adaptive and de-adaptive behaviors in both gaits. The posterior propulsive component, on the other hand, exhibited such behavior only in running, while that in walking showed only short-term aftereffect (lasting less than 10 seconds) accompanied by largely reactive responses. These results demonstrate a possible difference in motor strategies (that is, the use of reactive feedback and adaptive feedforward control) by the central nervous system (CNS) for split-belt locomotor adaptation between walking and running. The present results provide basic knowledge on neural control of human walking and running as well as possible strategies for gait training in athletic and rehabilitation scenes.

Distinct Motor Strategies Underlying Split-Belt Adaptation in Human Walking and Running

PubMed Central

Ogawa, Tetsuya; Kawashima, Noritaka; Obata, Hiroki; Kanosue, Kazuyuki; Nakazawa, Kimitaka

2015-01-01

The aim of the present study was to elucidate the adaptive and de-adaptive nature of human running on a split-belt treadmill. The degree of adaptation and de-adaptation was compared with those in walking by calculating the antero-posterior component of the ground reaction force (GRF). Adaptation to walking and running on a split-belt resulted in a prominent asymmetry in the movement pattern upon return to the normal belt condition, while the two components of the GRF showed different behaviors depending on the gaits. The anterior braking component showed prominent adaptive and de-adaptive behaviors in both gaits. The posterior propulsive component, on the other hand, exhibited such behavior only in running, while that in walking showed only short-term aftereffect (lasting less than 10 seconds) accompanied by largely reactive responses. These results demonstrate a possible difference in motor strategies (that is, the use of reactive feedback and adaptive feedforward control) by the central nervous system (CNS) for split-belt locomotor adaptation between walking and running. The present results provide basic knowledge on neural control of human walking and running as well as possible strategies for gait training in athletic and rehabilitation scenes. PMID:25775426

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

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

NASA Astrophysics Data System (ADS)

Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto; Takagi, Taro

2014-12-01

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

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.

PubMed

Najjar-Khodabakhsh, Abbas; Soltani, Jafar

2016-03-01

In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

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

Mizumoto, Ikuro; Nakamura, Takuto; Kumon, Makoto

2014-12-10

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

Effect of Roy's Adaptation Model-Guided Education on Coping Strategies of the Veterans with Lower Extremities Amputation: A Double-Blind Randomized Controlled Clinical Trial.

PubMed

Farsi, Zahra; Azarmi, Somayeh

2016-04-01

Any defect in the extremities of the body can affect different life aspects. The purpose of this study was to investigate the effect of Roy's adaptation model-guided education on coping strategies of the veterans with lower extremities amputation. In a double-blind randomized controlled clinical trial, 60 veterans with lower extremities amputation referring to Kowsar Orthotics and Prosthetics Center of Veterans Clinic in Tehran, Iran were recruited using convenience method and randomly assigned to intervention and control groups in 2013-2014. Lazarus and Folkman coping strategies questionnaire was used to collect the data. After completing the questionnaires in both groups, maladaptive behaviours were determined in the intervention group and an education program based on Roy's adaptation model was implemented. After 2 months, both groups completed the questionnaires again. Data were analyzed using SPSS software. Independent T-test showed that the score of the dimensions of coping strategies did not have a statistically significant difference between the intervention and control groups in the pre-intervention stage (P>0.05). This test showed a statistically significant difference between the two groups in the post-intervention stage in terms of the scores of different dimensions of coping strategies (P>0.05), except in dimensions of social support seeking and positive appraisal (P>0.05). The findings of this research indicated that the Roy's adaptation model-guided education improved the majority of coping strategies in veterans with lower extremities amputation. It is recommended that further interventions based on Roy's adaptation model should be performed to improve the coping of the veterans with lower extremities amputation. IRCT2014081118763N1.

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.

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

PubMed

Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

2012-08-01

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

An adaptive strategy for active debris removal

NASA Astrophysics Data System (ADS)

White, Adam E.; Lewis, Hugh G.

2014-04-01

Many parameters influence the evolution of the near-Earth debris population, including launch, solar, explosion and mitigation activities, as well as other future uncertainties such as advances in space technology or changes in social and economic drivers that effect the utilisation of space activities. These factors lead to uncertainty in the long-term debris population. This uncertainty makes it difficult to identify potential remediation strategies, involving active debris removal (ADR), that will perform effectively in all possible future cases. Strategies that cannot perform effectively, because of this uncertainty, risk either not achieving their intended purpose, or becoming a hindrance to the efforts of spacecraft manufactures and operators to address the challenges posed by space debris. One method to tackle this uncertainty is to create a strategy that can adapt and respond to the space debris population. This work explores the concept of an adaptive strategy, in terms of the number of objects required to be removed by ADR, to prevent the low Earth orbit (LEO) debris population from growing in size. This was demonstrated by utilising the University of Southampton’s Debris Analysis and Monitoring Architecture to the Geosynchronous Environment (DAMAGE) tool to investigate ADR rates (number of removals per year) that change over time in response to the current space environment, with the requirement of achieving zero growth of the LEO population. DAMAGE was used to generate multiple Monte Carlo projections of the future LEO debris environment. Within each future projection, the debris removal rate was derived at five-year intervals, by a new statistical debris evolutionary model called the Computational Adaptive Strategy to Control Accurately the Debris Environment (CASCADE) model. CASCADE predicted the long-term evolution of the current DAMAGE population with a variety of different ADR rates in order to identify a removal rate that produced a zero net

A Climate Change Adaptation Strategy for Management of ...

EPA Pesticide Factsheets

Sea level rise is causing shoreline erosion, increased coastal flooding, and marsh vulnerability to the impact of storms. Coastal marshes provide flood abatement, carbon and nutrient sequestration, water quality maintenance, and habitat for fish, shellfish, and wildlife, including species of concern, such as the saltmarsh sparrow (Ammodramus caudacutus). We present a climate change adaptation strategy (CCAS) adopted by scientific, management, and policy stakeholders for managing coastal marshes and enhancing system resiliency. A common adaptive management approach previously used for restoration projects was modified to identify climate-related vulnerabilities and plan climate change adaptive actions. As an example of implementation of the CCAS, we describe the stakeholder plans and management actions the US Fish and Wildlife Service and partners developed to build coastal resiliency in the Narrow River Estuary, RI, in the aftermath of Superstorm Sandy. When possible, an experimental BACI (before-after, control-impact) design, described as pre- and post-sampling at the impact site and one or more control sites, was incorporated into the climate change adaptation and implementation plans. Specific climate change adaptive actions and monitoring plans are described and include shoreline stabilization, restoring marsh drainage, increasing marsh elevation, and enabling upland marsh migration. The CCAS provides a framework and methodology for successfully managing coa

Employee stress management: An examination of adaptive and maladaptive coping strategies on employee health.

PubMed

Holton, M Kim; Barry, Adam E; Chaney, J Don

2015-01-01

Employees commonly report feeling stressed at work. Examine how employees cope with work and personal stress, whether their coping strategies are adaptive (protective to health) or maladaptive (detrimental to health), and if the manner in which employees cope with stress influences perceived stress management. In this cross-sectional study, a random sample of 2,500 full-time university non-student employees (i.e. faculty, salaried professionals, and hourly non-professionals) were surveyed on health related behaviors including stress and coping. Approximately 1,277 completed the survey (51% ). Hierarchical logistic regression was used to assess the ability of adaptive and maladaptive coping strategies to predict self-reported stress management, while controlling for multiple demographic variables. Over half of employees surveyed reported effective stress management. Most frequently used adaptive coping strategies were communication with friend/family member and exercise, while most frequently used maladaptive coping strategies were drinking alcohol and eating more than usual. Both adaptive and maladaptive coping strategies made significant (p < 0.05) contributions to predicting employee's perceived stress management. Only adaptive coping strategies (B = 0.265) predicted whether someone would self-identify as effectively managing stress. Use of maladaptive coping strategies decreased likelihood of self-reporting effective stress management. Actual coping strategies employed may influence employees' perceived stress management. Adaptive coping strategies may be more influential than maladaptive coping strategies on perceived stress management. Results illustrate themes for effective workplace stress management programs. Stress management programs focused on increasing use of adaptive coping may have a greater impact on employee stress management than those focused on decreasing use of maladaptive coping. Coping is not only a reaction to stressful experiences but also

Adaptive suboptimal second-order sliding mode control for microgrids

NASA Astrophysics Data System (ADS)

Incremona, Gian Paolo; Cucuzzella, Michele; Ferrara, Antonella

2016-09-01

This paper deals with the design of adaptive suboptimal second-order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second-order systems in Brunovsky canonical form, characterised by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analysed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies, the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state space of the auxiliary system becomes attractive. In the other two strategies, a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady state. The microgrid system in a grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

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.

Adapting qualitative research strategies to technology savvy adolescents.

PubMed

Mason, Deanna Marie; Ide, Bette

2014-05-01

To adapt research strategies involving adolescents in a grounded theory qualitative research study by conducting email rather than face-to-face interviews. Adolescent culture relies heavily on text-based communication and teens prefer interactions mediated through technology. Traditional qualitative research strategies need to be rethought when working with adolescents. Adapting interviewing strategies to electronic environments is timely and relevant for researching adolescents. Twenty three adolescents (aged 16-21) were interviewed by email. A letter of invitation was distributed. Potential participants emailed the researcher to convey interest in participating. If the inclusion criteria were met, email interviews were initiated. Participants controlled the interviews through their rate of response to interview questions. A grounded theory methodology was employed. Initial contact with participants reiterated confidentiality and the ability to withdraw from the study at any time. Interviews began with the collection of demographic information and a broad opening based on a semi-structured interview guide. All data were permissible, including text, photos, music, videos or outside media, for example YouTube. The participant was allowed to give direction to the interview after initial questions were posed. Email interviews continued until saturation was reached in the data. Participants were enthusiastic about email interviewing. Attrition did not occur. Email interviewing gave participants more control over the research, decreased power differentials between the adolescent and researcher, allowed the study to be adapted to cultural, linguistic and developmental needs, and maintained confidentiality. As participants said that email communication was slow and they preferred instant messaging, replication in faster-paced media is recommended. Repetition in face-to-face settings is warranted to evaluate how technology may have influenced the findings. Implications for

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.

Decentralized adaptive control

NASA Technical Reports Server (NTRS)

Oh, B. J.; Jamshidi, M.; Seraji, H.

1988-01-01

A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

Adaptive control of dynamical synchronization on evolving networks with noise disturbances

NASA Astrophysics Data System (ADS)

Yuan, Wu-Jie; Zhou, Jian-Fang; Sendiña-Nadal, Irene; Boccaletti, Stefano; Wang, Zhen

2018-02-01

In real-world networked systems, the underlying structure is often affected by external and internal unforeseen factors, making its evolution typically inaccessible. An adaptive strategy was introduced for maintaining synchronization on unpredictably evolving networks [Sorrentino and Ott, Phys. Rev. Lett. 100, 114101 (2008), 10.1103/PhysRevLett.100.114101], which yet does not consider the noise disturbances widely existing in networks' environments. We provide here strategies to control dynamical synchronization on slowly and unpredictably evolving networks subjected to noise disturbances which are observed at the node and at the communication channel level. With our strategy, the nodes' coupling strength is adaptively adjusted with the aim of controlling synchronization, and according only to their received signal and noise disturbances. We first provide a theoretical analysis of the control scheme by introducing an error potential function to seek for the minimization of the synchronization error. Then, we show numerical experiments which verify our theoretical results. In particular, it is found that our adaptive strategy is effective even for the case in which the dynamics of the uncontrolled network would be explosive (i.e., the states of all the nodes would diverge to infinity).

Adaptive disturbance compensation finite control set optimal control for PMSM systems based on sliding mode extended state observer

NASA Astrophysics Data System (ADS)

Wu, Yun-jie; Li, Guo-fei

2018-01-01

Based on sliding mode extended state observer (SMESO) technique, an adaptive disturbance compensation finite control set optimal control (FCS-OC) strategy is proposed for permanent magnet synchronous motor (PMSM) system driven by voltage source inverter (VSI). So as to improve robustness of finite control set optimal control strategy, a SMESO is proposed to estimate the output-effect disturbance. The estimated value is fed back to finite control set optimal controller for implementing disturbance compensation. It is indicated through theoretical analysis that the designed SMESO could converge in finite time. The simulation results illustrate that the proposed adaptive disturbance compensation FCS-OC possesses better dynamical response behavior in the presence of disturbance.

Adaptive Decentralized Control

DTIC Science & Technology

1985-04-01

and implementation of the decentralized controllers. It raises, however, many difficult questions regarding the conditions under which such a scheme ...adaptive controller, and a general form of the model reference adaptive controller (4]. We believe that this work represents a significant advance in the...Comparing the adaptive system with the tuned system results in the development of a generic adaptive error system. Passivity theory was used to derive

Online adaptation and over-trial learning in macaque visuomotor control.

PubMed

Braun, Daniel A; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning.

Adaptive process control using fuzzy logic and genetic algorithms

NASA Technical Reports Server (NTRS)

Karr, C. L.

1993-01-01

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

A multiple pointing-mount control strategy for space platforms

NASA Technical Reports Server (NTRS)

Johnson, C. D.

1992-01-01

A new disturbance-adaptive control strategy for multiple pointing-mount space platforms is proposed and illustrated by consideration of a simplified 3-link dynamic model of a multiple pointing-mount space platform. Simulation results demonstrate the effectiveness of the new platform control strategy. The simulation results also reveal a system 'destabilization phenomena' that can occur if the set of individual platform-mounted experiment controllers are 'too responsive.'

Precision-Based Item Selection for Exposure Control in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Carroll, Ian A.

2017-01-01

Item exposure control is, relative to adaptive testing, a nascent concept that has emerged only in the last two to three decades on an academic basis as a practical issue in high-stakes computerized adaptive tests. This study aims to implement a new strategy in item exposure control by incorporating the standard error of the ability estimate into…

The importance of training strategy adaptation: a learner-oriented approach for improving older adults' memory and transfer.

PubMed

Bottiroli, Sara; Cavallini, Elena; Dunlosky, John; Vecchi, Tomaso; Hertzog, Christopher

2013-09-01

We investigated the benefits of strategy-adaptation training for promoting transfer effects. This learner-oriented approach--which directly encourages the learner to generalize strategic behavior to new tasks--helps older adults appraise new tasks and adapt trained strategies to them. In Experiment 1, older adults in a strategy-adaptation training group used 2 strategies (imagery and sentence generation) while practicing 2 tasks (list and associative learning); they were then instructed on how to do a simple task analysis to help them adapt the trained strategies for 2 different unpracticed tasks (place learning and text learning) that were discussed during training. Two additional criterion tasks (name-face associative learning and grocery-list learning) were never mentioned during training. Two other groups were included: A strategy training group (who received strategy training and transfer instructions but not strategy-adaptation training) and a waiting-list control group. Both training procedures enhanced older adults' performance on the trained tasks and those tasks that were discussed during training, but transfer was greatest after strategy-adaptation training. Experiment 2 found that strategy-adaptation training conducted via a manual that older adults used at home also promoted transfer. These findings demonstrate the importance of adopting a learner-oriented approach to promote transfer of strategy training. PsycINFO Database Record (c) 2013 APA, all rights reserved.

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.

Adaptive fixed-time control for cluster synchronisation of coupled complex networks with uncertain disturbances

NASA Astrophysics Data System (ADS)

Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming

2017-12-01

This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

PubMed Central

Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

Paradoxical cardiovascular effects of implementing adaptive emotion regulation strategies in generalized anxiety disorder.

PubMed

Aldao, Amelia; Mennin, Douglas S

2012-02-01

Recent models of generalized anxiety disorder (GAD) have expanded on Borkovec's avoidance theory by delineating emotion regulation deficits associated with the excessive worry characteristic of this disorder (see Behar, DiMarco, Hekler, Mohlman, & Staples, 2009). However, it has been difficult to determine whether emotion regulation is simply a useful heuristic for the avoidant properties of worry or an important extension to conceptualizations of GAD. Some of this difficulty may arise from a focus on purported maladaptive regulation strategies, which may be confounded with symptomatic distress components of the disorder (such as worry). We examined the implementation of adaptive regulation strategies by participants with and without a diagnosis of GAD while watching emotion-eliciting film clips. In a between-subjects design, participants were randomly assigned to accept, reappraise, or were not given specific regulation instructions. Implementation of adaptive regulation strategies produced differential effects in the physiological (but not subjective) domain across diagnostic groups. Whereas participants with GAD demonstrated lower cardiac flexibility when implementing adaptive regulation strategies than when not given specific instructions on how to regulate, healthy controls showed the opposite pattern, suggesting they benefited from the use of adaptive regulation strategies. We discuss the implications of these findings for the delineation of emotion regulation deficits in psychopathology. Copyright © 2011 Elsevier Ltd. All rights reserved.

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

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

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.

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

PubMed

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

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.

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

PubMed Central

Zhu, Yunkai

2017-01-01

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

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

PubMed

Fei, Juntao; Zhu, Yunkai

2017-01-01

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

Adaptive fuzzy-neural-network control for maglev transportation system.

PubMed

Wai, Rong-Jong; Lee, Jeng-Dao

2008-01-01

A magnetic-levitation (maglev) transportation system including levitation and propulsion control is a subject of considerable scientific interest because of highly nonlinear and unstable behaviors. In this paper, the dynamic model of a maglev transportation system including levitated electromagnets and a propulsive linear induction motor (LIM) based on the concepts of mechanical geometry and motion dynamics is developed first. Then, a model-based sliding-mode control (SMC) strategy is introduced. In order to alleviate chattering phenomena caused by the inappropriate selection of uncertainty bound, a simple bound estimation algorithm is embedded in the SMC strategy to form an adaptive sliding-mode control (ASMC) scheme. However, this estimation algorithm is always a positive value so that tracking errors introduced by any uncertainty will cause the estimated bound increase even to infinity with time. Therefore, it further designs an adaptive fuzzy-neural-network control (AFNNC) scheme by imitating the SMC strategy for the maglev transportation system. In the model-free AFNNC, online learning algorithms are designed to cope with the problem of chattering phenomena caused by the sign action in SMC design, and to ensure the stability of the controlled system without the requirement of auxiliary compensated controllers despite the existence of uncertainties. The outputs of the AFNNC scheme can be directly supplied to the electromagnets and LIM without complicated control transformations for relaxing strict constrains in conventional model-based control methodologies. The effectiveness of the proposed control schemes for the maglev transportation system is verified by numerical simulations, and the superiority of the AFNNC scheme is indicated in comparison with the SMC and ASMC strategies.

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.

Direct adaptive control of wind energy conversion systems using Gaussian networks.

PubMed

Mayosky, M A; Cancelo, I E

1999-01-01

Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis zfunction network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution.

Complex adaptive therapeutic strategy (CATS) for cancer.

PubMed

Cho, Yong Woo; Kim, Sang Yoon; Kwon, Ick Chan; Kim, In-San

2014-02-10

Tumors begin with a single cell, but as each tumor grows and evolves, it becomes a wide collection of clones that display remarkable heterogeneity in phenotypic features, which has posed a big challenge to current targeted anticancer therapy. Intra- and inter-tumoral heterogeneity is attributable in part to genetic mutations but also to adaptation and evolution of tumors to heterogeneity in tumor microenvironments. If tumors are viewed not only as a disease but also as a complex adaptive system (CAS), tumors should be treated as such and a more systemic approach is needed. Some of many tumors therapeutic strategies are discussed here from a view of a tumor as CAS, which can be collectively called a complex adaptive therapeutic strategy (CATS). The central theme of CATS is based on three intermediate concepts: i) disruption of artifacts, ii) disruption of connections, and iii) reprogramming of cancer-immune dynamics. Each strategy presented here is a piece of the puzzle for CATS. Although each piece by itself may be neither novel nor profound, an assembled puzzle could be a novel and innovative cancer therapeutic strategy. Copyright © 2013 Elsevier B.V. All rights reserved.

Effects of Flood Control Strategies on Flood Resilience Under Sociohydrological Disturbances

NASA Astrophysics Data System (ADS)

Sung, Kyungmin; Jeong, Hanseok; Sangwan, Nikhil; Yu, David J.

2018-04-01

A community capacity to cope with flood hazards, or community flood resilience, emerges from the interplay of hydrological and social processes. This interplay can be significantly influenced by the flood control strategy adopted by a society, i.e., how a society sets its desired flood protection level and strives to achieve this goal. And this interplay can be further complicated by rising land-sea level differences, seasonal water level fluctuations, and economic change. But not much research has been done on how various forms of flood control strategies affect human-flood interactions under these disturbances and therefore flood resilience in the long run. The current study is an effort to address these issues by developing a conceptual model of human-flood interaction mediated by flood control strategies. Our model extends the existing model of Yu et al. (2017), who investigated the flood resilience of a community-based flood protection system in coastal Bangladesh. The major extensions made in this study are inclusions of various forms of flood control strategies (both adaptive and nonadaptive ones), the challenge of rising land-sea level differences, and various high tide level scenarios generated from modifying the statistical variances and averages. Our results show that adaptive forms of flood control strategies tend to outperform nonadaptive ones for maintaining the model community's flood protection system. Adaptive strategies that dynamically adjust target flood protection levels through close monitoring of flood damages and social memories of flood risk can help the model community deal with various disturbances.

Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure.

PubMed

Sun, Yumei; Chen, Bing; Lin, Chong; Wang, Honghong

2017-09-18

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.

Development of adaptive observation strategy using retrospective optimal interpolation

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Stepping strategies for regulating gait adaptability and stability.

PubMed

Hak, Laura; Houdijk, Han; Steenbrink, Frans; Mert, Agali; van der Wurff, Peter; Beek, Peter J; van Dieën, Jaap H

2013-03-15

Besides a stable gait pattern, gait in daily life requires the capability to adapt this pattern in response to environmental conditions. The purpose of this study was to elucidate the anticipatory strategies used by able-bodied people to attain an adaptive gait pattern, and how these strategies interact with strategies used to maintain gait stability. Ten healthy subjects walked in a Computer Assisted Rehabilitation ENvironment (CAREN). To provoke an adaptive gait pattern, subjects had to hit virtual targets, with markers guided by their knees, while walking on a self-paced treadmill. The effects of walking with and without this task on walking speed, step length, step frequency, step width and the margins of stability (MoS) were assessed. Furthermore, these trials were performed with and without additional continuous ML platform translations. When an adaptive gait pattern was required, subjects decreased step length (p<0.01), tended to increase step width (p=0.074), and decreased walking speed while maintaining similar step frequency compared to unconstrained walking. These adaptations resulted in the preservation of equal MoS between trials, despite the disturbing influence of the gait adaptability task. When the gait adaptability task was combined with the balance perturbation subjects further decreased step length, as evidenced by a significant interaction between both manipulations (p=0.012). In conclusion, able-bodied people reduce step length and increase step width during walking conditions requiring a high level of both stability and adaptability. Although an increase in step frequency has previously been found to enhance stability, a faster movement, which would coincide with a higher step frequency, hampers accuracy and may consequently limit gait adaptability. Copyright © 2012 Elsevier Ltd. All rights reserved.

Event-triggered decentralized adaptive fault-tolerant control of uncertain interconnected nonlinear systems with actuator failures.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2018-06-01

This paper investigates the event-triggered decentralized adaptive tracking problem of a class of uncertain interconnected nonlinear systems with unexpected actuator failures. It is assumed that local control signals are transmitted to local actuators with time-varying faults whenever predefined conditions for triggering events are satisfied. Compared with the existing control-input-based event-triggering strategy for adaptive control of uncertain nonlinear systems, the aim of this paper is to propose a tracking-error-based event-triggering strategy in the decentralized adaptive fault-tolerant tracking framework. The proposed approach can relax drastic changes in control inputs caused by actuator faults in the existing triggering strategy. The stability of the proposed event-triggering control system is analyzed in the Lyapunov sense. Finally, simulation comparisons of the proposed and existing approaches are provided to show the effectiveness of the proposed theoretical result in the presence of actuator faults. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Barrier Function-Based Neural Adaptive Control With Locally Weighted Learning and Finite Neuron Self-Growing Strategy.

PubMed

Jia, Zi-Jun; Song, Yong-Duan

2017-06-01

This paper presents a new approach to construct neural adaptive control for uncertain nonaffine systems. By integrating locally weighted learning with barrier Lyapunov function (BLF), a novel control design method is presented to systematically address the two critical issues in neural network (NN) control field: one is how to fulfill the compact set precondition for NN approximation, and the other is how to use varying rather than a fixed NN structure to improve the functionality of NN control. A BLF is exploited to ensure the NN inputs to remain bounded during the entire system operation. To account for system nonlinearities, a neuron self-growing strategy is proposed to guide the process for adding new neurons to the system, resulting in a self-adjustable NN structure for better learning capabilities. It is shown that the number of neurons needed to accomplish the control task is finite, and better performance can be obtained with less number of neurons as compared with traditional methods. The salient feature of the proposed method also lies in the continuity of the control action everywhere. Furthermore, the resulting control action is smooth almost everywhere except for a few time instants at which new neurons are added. Numerical example illustrates the effectiveness of the proposed approach.

Control architecture for an adaptive electronically steerable flash lidar and associated instruments

NASA Astrophysics Data System (ADS)

Ruppert, Lyle; Craner, Jeremy; Harris, Timothy

2014-09-01

An Electronically Steerable Flash Lidar (ESFL), developed by Ball Aerospace & Technologies Corporation, allows realtime adaptive control of configuration and data-collection strategy based on recent or concurrent observations and changing situations. This paper reviews, at a high level, some of the algorithms and control architecture built into ESFL. Using ESFL as an example, it also discusses the merits and utility such adaptable instruments in Earth-system studies.

Enhancing TSM&O strategies through life cycle benefit/cost analysis : life cycle benefit/cost analysis & life cycle assessment of adaptive traffic control systems and ramp metering systems.

DOT National Transportation Integrated Search

2015-05-01

The research team developed a comprehensive Benefit/Cost (B/C) analysis framework to evaluate existing and anticipated : intelligent transportation system (ITS) strategies, particularly, adaptive traffic control systems and ramp metering systems, : i...

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.

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.

Parallel computations and control of adaptive structures

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle.

PubMed

Peng, Jiankun; He, Hongwen; Liu, Wei; Guo, Hongqiang

2015-01-01

This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved.

Hierarchical Control Strategy for the Cooperative Braking System of Electric Vehicle

PubMed Central

Peng, Jiankun; He, Hongwen; Guo, Hongqiang

2015-01-01

This paper provides a hierarchical control strategy for cooperative braking system of an electric vehicle with separated driven axles. Two layers are defined: the top layer is used to optimize the braking stability based on two sliding mode control strategies, namely, the interaxle control mode and signal-axle control strategies; the interaxle control strategy generates the ideal braking force distribution in general braking condition, and the single-axle control strategy can ensure braking safety in emergency braking condition; the bottom layer is used to maximize the regenerative braking energy recovery efficiency with a reallocated braking torque strategy; the reallocated braking torque strategy can recovery braking energy as much as possible in the premise of meeting battery charging power. The simulation results show that the proposed hierarchical control strategy is reasonable and can adapt to different typical road surfaces and load cases; the vehicle braking stability and safety can be guaranteed; furthermore, the regenerative braking energy recovery efficiency can be improved. PMID:26236772

Nutritional strategies to influence adaptations to training.

PubMed

Spriet, Lawrence L; Gibala, Martin J

2004-01-01

This article highlights new nutritional concerns or practices that may influence the adaptation to training. The discussion is based on the assumption that the adaptation to repeated bouts of training occurs during recovery periods and that if one can train harder, the adaptation will be greater. The goal is to maximize with nutrition the recovery/adaptation that occurs in all rest periods, such that recovery before the next training session is complete. Four issues have been identified where recent scientific information will force sports nutritionists to embrace new issues and reassess old issues and, ultimately, alter the nutritional recommendations they give to athletes. These are: (1) caffeine ingestion; (2) creatine ingestion; (3) the use of intramuscular triacylglycerol (IMTG) as a fuel during exercise and the nutritional effects on IMTG repletion following exercise; and (4) the role nutrition may play in regulating the expression of genes during and after exercise training sessions. Recent findings suggest that low doses of caffeine exert significant ergogenic effects by directly affecting the central nervous system during exercise. Caffeine can cross the blood-brain barrier and antagonize the effects of adenosine, resulting in higher concentrations of stimulatory neurotransmitters. These new data strengthen the case for using low doses of caffeine during training. On the other hand, the data on the role that supplemental creatine ingestion plays in augmenting the increase in skeletal muscle mass and strength during resistance training remain equivocal. Some studies are able to demonstrate increases in muscle fibre size with creatine ingestion and some are not. The final two nutritional topics are new and have not progressed to the point that we can specifically identify strategies to enhance the adaptation to training. However, it is likely that nutritional strategies will be needed to replenish the IMTG that is used during endurance exercise. It is not

Variable Neural Adaptive Robust Control: A Switched System Approach

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

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

2015-05-01

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

TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

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

Boeck, M; KTH Royal Institute of Technology, Stockholm; Eriksson, K

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errorsmore » on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in

Multigrid solution strategies for adaptive meshing problems

NASA Technical Reports Server (NTRS)

Mavriplis, Dimitri J.

1995-01-01

This paper discusses the issues which arise when combining multigrid strategies with adaptive meshing techniques for solving steady-state problems on unstructured meshes. A basic strategy is described, and demonstrated by solving several inviscid and viscous flow cases. Potential inefficiencies in this basic strategy are exposed, and various alternate approaches are discussed, some of which are demonstrated with an example. Although each particular approach exhibits certain advantages, all methods have particular drawbacks, and the formulation of a completely optimal strategy is considered to be an open problem.

Active control strategy for the running attitude of high-speed train under strong crosswind condition

NASA Astrophysics Data System (ADS)

Li, Decang; Meng, Jianjun; Bai, Huan; Xu, Ruxun

2018-07-01

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host-target computer technology provided by Matlab/Simulink.

Adaptive control of 5 DOF upper-limb exoskeleton robot with improved safety.

PubMed

Kang, Hao-Bo; Wang, Jian-Hui

2013-11-01

This paper studies an adaptive control strategy for a class of 5 DOF upper-limb exoskeleton robot with a special safety consideration. The safety requirement plays a critical role in the clinical treatment when assisting patients with shoulder, elbow and wrist joint movements. With the objective of assuring the tracking performance of the pre-specified operations, the proposed adaptive controller is firstly designed to be robust to the model uncertainties. To further improve the safety and fault-tolerance in the presence of unknown large parameter variances or even actuator faults, the adaptive controller is on-line updated according to the information provided by an adaptive observer without additional sensors. An output tracking performance is well achieved with a tunable error bound. The experimental example also verifies the effectiveness of the proposed control scheme. © 2013 ISA. Published by ISA. All rights reserved.

Self-guided strategy-adaption training for older adults: Transfer effects to everyday tasks.

PubMed

Bottiroli, Sara; Cavallini, Elena; Dunlosky, John; Vecchi, Tomaso; Hertzog, Christopher

2017-09-01

The goal of the present research was to examine the potential of a learner-oriented approach to improving older adults' performance in tasks that are similar to real-life situations that require strategic deployment of cognitive resources. A crucial element of this approach involves encouraging older adults to explicitly analyze tasks to consider how to adapt trained skills to a new task context. In an earlier study, a specialist-directed intervention produced training gains and transfer to some untrained memory tasks. In the present study, older adults received a manual instructing them about principles of task analysis, two memory strategies, and strategy adaptation. Self-guided strategy-adaption training involved practicing some memory tasks as well as instructions on how the trained skills could be applied to new tasks that were not practiced. The criterion tasks involved practice tasks, non-practiced tasks that were discussed in the manual, and transfer tasks that were never mentioned in the manual. Two of the tests were from the Everyday Cognition Battery (inductive reasoning and working memory). As compared to a waiting-list control group, older adults assigned to self-guided strategy-adaption training showed memory improvements on tasks that were practiced or discussed during training. Most important, the learner-oriented approach produced transfer to the everyday tasks. Our findings show the potential of instructing task appraisal processes as a basis for fostering transfer, including improving older adults' performance in simulated everyday tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive control applied to Space Station attitude control system

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Optimal and Adaptive Control of Flow in a Thermal Convection Loop

NASA Astrophysics Data System (ADS)

Yuen, Po Ki; Bau, Haim

1998-11-01

In theory and experiment, we use nonlinear and linear optimal and adaptive controllers to suppress the naturally occurring chaotic convection in a thermal convection loop. The thermal convection loop is a simple experimental analog of the Lorenz equations, and it provides a convenient platform for testing and comparing the performance of various control strategies in a fluid mechanical setting. The performance of the optimal and adaptive controllers is compared with that of a previously developed simple feedback controller (Singer, J., Wang, Y., & Bau, H., H., 1991, Physical Review Letters, 66,123-1125.)(Wang, Y., Singer, J., & Bau, H., H., 1992, J. Fluid Mechanics, 237, 479-498.), a nonlinear controller with a cubic nonlinearity(Yuen, P., & Bau, H., H., 1996, J. Fluid Mechanics, 317, 91-109.), and a neural net controller(Yuen, P., & Bau, H., H., 1998, Neural Networks, 11, 557 - 569, 1998.). It is demonstrated that an adaptive controller can perform successfully even when the system's model is not known.

A reduced energy supply strategy in active vibration control

NASA Astrophysics Data System (ADS)

Ichchou, M. N.; Loukil, T.; Bareille, O.; Chamberland, G.; Qiu, J.

2011-12-01

In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings.

[Coping strategies in adaptation of higher education students].

PubMed

das Neves Mira Freitas, Helena Cristina

2007-01-01

The adjustment to higher education can be understood as a multidimensional process, which requires by the student a development of adaptive skills to a new and dynamic context in itself. To meet these challenges students have to develop effective coping strategies, enabling them to be adapted to the context. The school has a key role in the help it can give to these young people, in order to adapt effectively.

Decentralized adaptive control of robot manipulators with robust stabilization design

NASA Technical Reports Server (NTRS)

Yuan, Bau-San; Book, Wayne J.

1988-01-01

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

Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.

PubMed

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

2017-06-01

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.

Managing Work and Family: Do Control Strategies Help?

ERIC Educational Resources Information Center

Versey, H. Shellae

2015-01-01

How can we effectively manage competing obligations from work and family without becoming overwhelmed? This question inspires the current study by examining control strategies that may facilitate better work-life balance, with a specific focus on the role of lowered aspirations and positive reappraisals, attitudes that underlie adaptive coping…

Cognitive emotion regulation strategies in patients with functional dyspepsia and healthy controls - A comparative study

PubMed Central

Mazaheri, Mina; Afshar, Hamid; Nikneshan, Shekoufeh; Adibi, Peyman

2016-01-01

Background: Patients with functional dyspepsia (FD) may use specific coping strategies. Hence, the aim of the present study was to compare cognitive emotion regulation strategies in FD patients and healthy controls. Materials and Methods: This was a descriptive observational study. The sample consisted of 86 individuals, 43 of whom were patients diagnosed with FD. The patients referred to the psychosomatic disorders clinic, Isfahan, Iran. The comparative sample included 43 healthy controls (without digestive diagnoses) matched with the patients by age and gender. Subjects completed data on demographic factors and cognitive emotion regulation questionnaire. Results: The results indicated that there are significant differences between patients with FD and healthy controls according to using cognitive strategies. Scores of healthy controls in positive reappraisal and acceptance were significantly more than FD patients, and inversely, scores of FD patients in rumination and other-blame were meaningfully more than healthy controls. Conclusion: FD patients apply less adaptive strategies and more maladaptive strategies. It is seemed psychological interventions that focus on reducing maladaptive strategies and increasing adaptive strategies could be effective for FD patients. PMID:28217634

Adaptive hybrid control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

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

Adaptive control of robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

Dosimetric advantages of a clinical daily adaptive plan selection strategy compared with a non-adaptive strategy in cervical cancer radiation therapy.

PubMed

van de Schoot, Agustinus J A J; de Boer, Peter; Visser, Jorrit; Stalpers, Lukas J A; Rasch, Coen R N; Bel, Arjan

2017-05-01

Radiation therapy (RT) using a daily plan selection adaptive strategy can be applied to account for interfraction organ motion while limiting organ at risk dose. The aim of this study was to quantify the dosimetric consequences of daily plan selection compared with non-adaptive RT in cervical cancer. Ten consecutive patients who received pelvic irradiation, planning CTs (full and empty bladder), weekly post-fraction CTs and pre-fraction CBCTs were included. Non-adaptive plans were generated based on the PTV defined using the full bladder planning CT. For the adaptive strategy, multiple PTVs were created based on both planning CTs by ITVs of the primary CTVs (i.e., GTV, cervix, corpus-uterus and upper part of the vagina) and corresponding library plans were generated. Daily CBCTs were rigidly aligned to the full bladder planning CT for plan selection. For daily plan recalculation, selected CTs based on initial similarity were deformably registered to CBCTs. Differences in daily target coverage (D 98%  > 95%) and in V 0.5Gy , V 1.5Gy , V 2Gy , D 50% and D 2% for rectum, bladder and bowel were assessed. Non-adaptive RT showed inadequate primary CTV coverage in 17% of the daily fractions. Plan selection compensated for anatomical changes and improved primary CTV coverage significantly (p < 0.01) to 98%. Compared with non-adaptive RT, plan selection decreased the fraction dose to rectum and bowel indicated by significant (p < 0.01) improvements for daily V 0.5Gy , V 1.5Gy , V 2Gy , D 50% and D 2% . However, daily plan selection significantly increased the bladder V 1.5Gy , V 2Gy , D 50% and D 2% . In cervical cancer RT, a non-adaptive strategy led to inadequate target coverage for individual patients. Daily plan selection corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions. The dose to bowel and rectum was decreased significantly when applying adaptive RT.

Functional specialization in regulation and quality control in thermal adaptive evolution.

PubMed

Yama, Kazuma; Matsumoto, Yuki; Murakami, Yoshie; Seno, Shigeto; Matsuda, Hideo; Gotoh, Kazuyoshi; Motooka, Daisuke; Nakamura, Shota; Ying, Bei-Wen; Yomo, Tetsuya

2015-11-01

Distinctive survival strategies, specialized in regulation and in quality control, were observed in thermal adaptive evolution with a laboratory Escherichia coli strain. The two specialists carried a single mutation either within rpoH or upstream of groESL, which led to the activated global regulation by sigma factor 32 or an increased amount of GroEL/ES chaperonins, respectively. Although both specialists succeeded in thermal adaptation, the common winner of the evolution was the specialist in quality control, that is, the strategy of chaperonin-mediated protein folding. To understand this evolutionary consequence, multilevel analyses of cellular status, for example, transcriptome, protein and growth fitness, were carried out. The specialist in quality control showed less change in transcriptional reorganization responding to temperature increase, which was consistent with the finding of that the two specialists showed the biased expression of molecular chaperones. Such repressed changes in gene expression seemed to be advantageous for long-term sustainability because a specific increase in chaperonins not only facilitated the folding of essential gene products but also saved cost in gene expression compared with the overall transcriptional increase induced by rpoH regulation. Functional specialization offered two strategies for successful thermal adaptation, whereas the evolutionary advantageous was more at the points of cost-saving in gene expression and the essentiality in protein folding. © 2015 The Authors. Genes to Cells published by Molecular Biology Society of Japan and Wiley Publishing Asia Pty Ltd.

A dual-loop adaptive control for minimizing time response delay in real-time structural vibration control with magnetorheological (MR) devices

NASA Astrophysics Data System (ADS)

Chen, Xi; Li, Yancheng; Li, Jianchun; Gu, Xiaoyu

2018-01-01

Time delay is a challenge issue faced by the real-time control application of the magnetorheological (MR) devices. Not to deal with it properly may jeopardize the effectiveness of the control, even lead to instability of the control system or catastrophic failure. This paper proposes a dual-loop adaptive control to address the response time delay associated with MR devices. In the proposed dual-loop control, the inner loop is designed to compensate the time delay of MR device induced by the PWM current driver. While the outer loop control can be any structural control algorithm with aims to reducing structural responses of a building during extreme loadings. Here an adaptive control strategy is adopted. To verify the proposed dual-loop control, a smart base isolation system employing magnetorheological elastomer base isolators is used as an example to illustrate the control effect. Numerical study is then conducted using a 5 -storey shear building model equipped with smart base isolation system. The result shows that with the implementation of the inner loop, the control current can instantly follow the control command which reduce the possibility of instability caused by the time delay. Comparative studies are conducted between three control strategies, i.e. dual-loop control, Lyapunov’s direct method based control and optimal passive base isolation control. The results of the study have demonstrated that the proposed dual-loop control strategy can achieve much better performance than the other two control strategies.

Genic Variability and Strategies of Adaptation in Animals

PubMed Central

Selander, Robert K.; Kaufman, Donald W.

1973-01-01

Levels of genic heterozygosity, as measured by surveys of allozymic variation, are much lower in populations of large, mobile animals (most vertebrates) than in those of small, relatively immobile animals (most invertebrates). This difference is not consistent with theories relating variability to population size (species number) or dispersal ability (gene flow), but it is predicted by Levins' theory of adaptive strategies in relation to environmental uncertainty (“grain”). Mobility and degree of homeostatic control apparently are important factors influencing levels of genic heterozygosity in natural populations. The results argue indirectly that at least a major proportion of allozymic variation is maintained by natural selection. PMID:4515944

Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Matsutani, Megumi; Annaswamy, Anuradha M.

2010-01-01

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

The use of modelling to evaluate and adapt strategies for animal disease control.

PubMed

Saegerman, C; Porter, S R; Humblet, M F

2011-08-01

Disease is often associated with debilitating clinical signs, disorders or production losses in animals and/or humans, leading to severe socio-economic repercussions. This explains the high priority that national health authorities and international organisations give to selecting control strategies for and the eradication of specific diseases. When a control strategy is selected and implemented, an effective method of evaluating its efficacy is through modelling. To illustrate the usefulness of models in evaluating control strategies, the authors describe several examples in detail, including three examples of classification and regression tree modelling to evaluate and improve the early detection of disease: West Nile fever in equids, bovine spongiform encephalopathy (BSE) and multifactorial diseases, such as colony collapse disorder (CCD) in the United States. Also examined are regression modelling to evaluate skin test practices and the efficacy of an awareness campaign for bovine tuberculosis (bTB); mechanistic modelling to monitor the progress of a control strategy for BSE; and statistical nationwide modelling to analyse the spatio-temporal dynamics of bTB and search for potential risk factors that could be used to target surveillance measures more effectively. In the accurate application of models, an interdisciplinary rather than a multidisciplinary approach is required, with the fewest assumptions possible.

Adaptive control of periodic systems

NASA Astrophysics Data System (ADS)

Tian, Zhiling

2009-12-01

Adaptive control is needed to cope with parametric uncertainty in dynamical systems. The adaptive control of LTI systems in both discrete and continuous time has been studied for four decades and the results are currently used widely in many different fields. In recent years, interest has shifted to the adaptive control of time-varying systems. It is known that the adaptive control of arbitrarily rapidly time-varying systems is in general intractable, but systems with periodically time-varying parameters (LTP systems) which have much more structure, are amenable to mathematical analysis. Further, there is also a need for such control in practical problems which have arisen in industry during the past twenty years. This thesis is the first attempt to deal with the adaptive control of LTP systems. Adaptive Control involves estimation of unknown parameters, adjusting the control parameters based on the estimates, and demonstrating that the overall system is stable. System theoretic properties such as stability, controllability, and observability play an important role both in formulating of the problems, as well as in generating solutions for them. For LTI systems, these properties have been studied since 1960s, and algebraic conditions that have to be satisfied to assure these properties are now well established. In the case of LTP systems, these properties can be expressed only in terms of transition matrices that are much more involved than those for LTI systems. Since adaptive control problems can be formulated only when these properties are well understood, it is not surprising that systematic efforts have not been made thus far for formulating and solving adaptive control problems that arise in LTP systems. Even in the case of LTI systems, it is well recognized that problems related to adaptive discrete-time system are not as difficult as those that arise in the continuous-time systems. This is amply evident in the solutions that were derived in the 1980s and

Competition and time-dependent behavior in spatial iterated prisoner’s dilemma incorporating adaptive zero-determinant strategies

NASA Astrophysics Data System (ADS)

Li, Yong; Xu, Chen; Liu, Jie; Hui, Pak Ming

2016-10-01

We propose and study the competitiveness of a class of adaptive zero-determinant strategies (ZDSs) in a population with spatial structure against four classic strategies in iterated prisoner’s dilemma. Besides strategy updating via a probabilistic mechanism by imitating the strategy of a better performing opponent, players using the ZDSs can also adapt their strategies to take advantage of their local competing environment with another probability. The adapted ZDSs could be extortionate-like to avoid being continually cheated by defectors or to take advantage of unconditional cooperators. The adapted ZDSs could also be a compliance strategy so as to cooperate with the conditionally cooperative players. This flexibility makes adaptive ZDSs more competitive than nonadaptive ZDSs. Results show that adaptive ZDSs can either dominate over other strategies or at least coexist with them when the ZDSs are allowed to adapt more readily than to imitate other strategies. The effectiveness of the adaptive ZDSs relies on how fast they can adapt to the competing environment before they are replaced by other strategies. The adaptive ZDSs generally work well as they could adapt gradually and make use of other strategies for suppressing their enemies. When adaptation happens more readily than imitation for the ZDSs, they outperform other strategies over a wide range of cost-to-benefit ratios.

Growing assisted migration: Synthesis of a climate change adaptation strategy

Treesearch

Mary I. Williams; R. Kasten Dumroese

2013-01-01

Assisted migration may be necessary as a climate change adaptation strategy for native plant species that are less adaptive or mobile. Moving plants has been practiced a long time in human history, but movement of species in response to climate change is a new context. First proposed in 1985, assisted migration has gained attention since 2007 as a strategy to prevent...

Nonlinear discrete-time multirate adaptive control of non-linear vibrations of smart beams

NASA Astrophysics Data System (ADS)

Georgiou, Georgios; Foutsitzi, Georgia A.; Stavroulakis, Georgios E.

2018-06-01

The nonlinear adaptive digital control of a smart piezoelectric beam is considered. It is shown that in the case of a sampled-data context, a multirate control strategy provides an appropriate framework in order to achieve vibration regulation, ensuring the stability of the whole control system. Under parametric uncertainties in the model parameters (damping ratios, frequencies, levels of non linearities and cross coupling, control input parameters), the scheme is completed with an adaptation law deduced from hyperstability concepts. This results in the asymptotic satisfaction of the control objectives at the sampling instants. Simulation results are presented.

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Adaptive control of base-isolated buildings using piezoelectric friction dampers against near-field earthquakes

NASA Astrophysics Data System (ADS)

Bitaraf, Maryam; Ozbulut, Osman E.; Hurlebaus, Stefan

2010-04-01

This paper investigates the effectiveness of two adaptive control strategies for modulating control force of piezoelectric friction dampers (PFDs) that are employed as semi-active devices in combination with laminated rubber bearings for seismic protection of buildings. The first controller developed in this study is a direct adaptive fuzzy logic controller. It consists of an upper-level and a sub-level direct fuzzy controller. In the hierarchical control scheme, higher-level controller modifies universe of discourse of both premise and consequent variables of the sub-level controller using scaling factors in order to determine command voltage of the damper according to current level of ground motion. The sub-level fuzzy controller employs isolation displacement and velocity as its premise variables and command voltage as its consequent variable. The second controller is based on the simple adaptive control (SAC) method, which is a type of direct adaptive control approach. The objective of the SAC method is to make the plant, the controlled system, track the behavior of the structure with the optimum performance. By using SAC strategy, any change in the characteristics of the structure or uncertainties in the modeling of the structure and in the external excitation would be considered because it continuously monitors its own performance to modify its parameters. Here, SAC methodology is employed to obtain the required force which results in the optimum performance of the structure. Then, the command voltage of the PFD is determined to generate the desired force. For comparison purposes, an optimal controller is also developed and considered in the simulations together with maximum passive operation of the friction damper. Time-history analyses of a base-isolated five-story building are performed to evaluate the performance of the controllers. Results reveal that developed adaptive controllers can successfully improve seismic response of the base-isolated buildings

Finite-Time Stabilization and Adaptive Control of Memristor-Based Delayed Neural Networks.

PubMed

Wang, Leimin; Shen, Yi; Zhang, Guodong

Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.

Adaptive Fuzzy Bounded Control for Consensus of Multiple Strict-Feedback Nonlinear Systems.

PubMed

Wang, Wei; Tong, Shaocheng

2018-02-01

This paper studies the adaptive fuzzy bounded control problem for leader-follower multiagent systems, where each follower is modeled by the uncertain nonlinear strict-feedback system. Combining the fuzzy approximation with the dynamic surface control, an adaptive fuzzy control scheme is developed to guarantee the output consensus of all agents under directed communication topologies. Different from the existing results, the bounds of the control inputs are known as a priori, and they can be determined by the feedback control gains. To realize smooth and fast learning, a predictor is introduced to estimate each error surface, and the corresponding predictor error is employed to learn the optimal fuzzy parameter vector. It is proved that the developed adaptive fuzzy control scheme guarantees the uniformly ultimate boundedness of the closed-loop systems, and the tracking error converges to a small neighborhood of the origin. The simulation results and comparisons are provided to show the validity of the control strategy presented in this paper.

Linking Federal, State, and Local Adaptation Strategies in New York (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2010-12-01

New York City and New York State are leaders in adaptation in the U.S. In 2008 Mayor Bloomberg convened the NYC Climate Change Adaptation Task Force and the New York City Panel on Climate Change (NPCC). Also in 2008, the New York State Energy Research and Development Authority (NYSERDA) initiated the Integrated Assessment for Effective Climate Change Adaptation Strategies (ClimAID), to provide New York State decision-makers with cutting-edge information on its vulnerability to climate change and to facilitate the development of adaptation strategies informed by both local experience and scientific knowledge. The two efforts are working together to develop effective adaptation strategies across multiple jurisdictions. The New York Task Force consists of approximate 40 city, state, and federal agencies, regional public authorities, and private companies that operate, maintain, or regulate critical infrastructure in the region. The NPCC consisted of climate change and impacts scientists, and legal, insurance, and risk-management experts and served as the technical advisory body for the Mayor and the Task Force on issues related to climate change, impacts, and adaptation. In its 2010 report, the NPCC recommended adoption of a risk-based approach to climate change; creation of a monitoring program to track and analyze key climate change factors, impacts, and adaptation indicators; review of relevant standards and codes; inclusion of multiple layers of government and a wide range of public and private stakeholder experts to build buy-in; and formation of crucial partnerships for development of coordinated adaptation strategies. The task now is for these partnerships to create pilot programs that move adaptation from the planning phase to implementation; urban areas can provide critical ‘test-beds’ for such efforts.

Investigation of energy management strategies for photovoltaic systems - A predictive control algorithm

NASA Technical Reports Server (NTRS)

Cull, R. C.; Eltimsahy, A. H.

1983-01-01

The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.

Assessment of the effectiveness of flood adaptation strategies for HCMC

NASA Astrophysics Data System (ADS)

Lasage, R.; Veldkamp, T. I. E.; de Moel, H.; Van, T. C.; Phi, H. L.; Vellinga, P.; Aerts, J. C. J. H.

2014-06-01

Coastal cities are vulnerable to flooding, and flood risk to coastal cities will increase due to sea-level rise. Moreover, Asian cities in particular are subject to considerable population growth and associated urban developments, increasing this risk even more. Empirical data on vulnerability and the cost and benefits of flood risk reduction measures are therefore paramount for sustainable development of these cities. This paper presents an approach to explore the impacts of sea-level rise and socio-economic developments on flood risk for the flood-prone District 4 in Ho Chi Minh City, Vietnam, and to develop and evaluate the effects of different adaptation strategies (new levees, dry- and wet proofing of buildings and elevating roads and buildings). A flood damage model was developed to simulate current and future flood risk using the results from a household survey to establish stage-damage curves for residential buildings. The model has been used to assess the effects of several participatory developed adaptation strategies to reduce flood risk, expressed in expected annual damage (EAD). Adaptation strategies were evaluated assuming combinations of both sea-level scenarios and land-use scenarios. Together with information on costs of these strategies, we calculated the benefit-cost ratio and net present value for the adaptation strategies until 2100, taking into account depreciation rates of 2.5% and 5%. The results of this modelling study indicate that the current flood risk in District 4 is USD 0.31 million per year, increasing up to USD 0.78 million per year in 2100. The net present value and benefit-cost ratios using a discount rate of 5 % range from USD -107 to -1.5 million, and from 0.086 to 0.796 for the different strategies. Using a discount rate of 2.5% leads to an increase in both net present value and benefit-cost ratio. The adaptation strategies wet-proofing and dry-proofing generate the best results using these economic indicators. The information

Review of control strategies for robotic movement training after neurologic injury.

PubMed

Marchal-Crespo, Laura; Reinkensmeyer, David J

2009-06-16

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.

Review of control strategies for robotic movement training after neurologic injury

PubMed Central

Marchal-Crespo, Laura; Reinkensmeyer, David J

2009-01-01

There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies. PMID:19531254

Strategies to intervene on causal systems are adaptively selected.

PubMed

Coenen, Anna; Rehder, Bob; Gureckis, Todd M

2015-06-01

How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e. possible causal structures). We compare this discriminatory model to a positive testing strategy that instead aims to confirm individual hypotheses. Experiment 1 shows that individual behavior is described best by a mixture of these two alternatives. In Experiment 2 we find that people are able to adaptively alter their behavior and adopt the discriminatory model more often after experiencing that the confirmatory strategy leads to a subjective performance decrement. In Experiment 3, time pressure leads to the opposite effect of inducing a change towards the simpler positive testing strategy. These findings suggest that there is no single strategy that describes how intervention decisions are made. Instead, people select strategies in an adaptive fashion that trades off their expected performance and cognitive effort. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

PubMed

Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

2017-07-01

In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

Two biomechanical strategies for locomotor adaptation to split-belt treadmill walking in subjects with and without transtibial amputation.

PubMed

Selgrade, Brian P; Toney, Megan E; Chang, Young-Hui

2017-02-28

Locomotor adaptation is commonly studied using split-belt treadmill walking, in which each foot is placed on a belt moving at a different speed. As subjects adapt to split-belt walking, they reduce metabolic power, but the biomechanical mechanism behind this improved efficiency is unknown. Analyzing mechanical work performed by the legs and joints during split-belt adaptation could reveal this mechanism. Because ankle work in the step-to-step transition is more efficient than hip work, we hypothesized that control subjects would reduce hip work on the fast belt and increase ankle work during the step-to-step transition as they adapted. We further hypothesized that subjects with unilateral, trans-tibial amputation would instead increase propulsive work from their intact leg on the slow belt. Control subjects reduced hip work and shifted more ankle work to the step-to-step transition, supporting our hypothesis. Contrary to our second hypothesis, intact leg work, ankle work and hip work in amputees were unchanged during adaptation. Furthermore, all subjects increased collisional energy loss on the fast belt, but did not increase propulsive work. This was possible because subjects moved further backward during fast leg single support in late adaptation than in early adaptation, compensating by reducing backward movement in slow leg single support. In summary, subjects used two strategies to improve mechanical efficiency in split-belt walking adaptation: a CoM displacement strategy that allows for less forward propulsion on the fast belt; and, an ankle timing strategy that allows efficient ankle work in the step-to-step transition to increase while reducing inefficient hip work. Copyright © 2017 Elsevier Ltd. All rights reserved.

An adaptable navigation strategy for Virtual Microscopy from mobile platforms.

PubMed

Corredor, Germán; Romero, Eduardo; Iregui, Marcela

2015-04-01

Real integration of Virtual Microscopy with the pathologist service workflow requires the design of adaptable strategies for any hospital service to interact with a set of Whole Slide Images. Nowadays, mobile devices have the actual potential of supporting an online pervasive network of specialists working together. However, such devices are still very limited. This article introduces a novel highly adaptable strategy for streaming and visualizing WSI from mobile devices. The presented approach effectively exploits and extends the granularity of the JPEG2000 standard and integrates it with different strategies to achieve a lossless, loosely-coupled, decoder and platform independent implementation, adaptable to any interaction model. The performance was evaluated by two expert pathologists interacting with a set of 20 virtual slides. The method efficiently uses the available device resources: the memory usage did not exceed a 7% of the device capacity while the decoding times were smaller than the 200 ms per Region of Interest, i.e., a window of 256×256 pixels. This model is easily adaptable to other medical imaging scenarios. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of cognitive control training on the dynamics of (mal)adaptive emotion regulation in daily life.

PubMed

Hoorelbeke, Kristof; Koster, Ernst H W; Demeyer, Ineke; Loeys, Tom; Vanderhasselt, Marie-Anne

2016-10-01

Cognitive control plays a key role in both adaptive emotion regulation, such as positive reappraisal, and maladaptive emotion regulation, such as rumination, with both strategies playing a major role in resilience and well-being. As a result, cognitive control training (CCT) targeting working memory functioning may have the potential to reduce maladaptive emotion regulation and increase adaptive emotion regulation. The current study explored the effects of CCT on positive reappraisal ability in a lab context, and deployment and efficacy of positive appraisal and rumination in daily life. A sample of undergraduates (n = 83) was allocated to CCT or an active control condition, performing 10 online training sessions over a period of 14 days. Effects on regulation of affective states in daily life were assessed using experience sampling over a 7-day posttraining period. Results revealed a positive association between baseline cognitive control and self-reported use of adaptive emotion regulation strategies, whereas maladaptive emotion regulation strategies showed a negative association. CCT showed transfer to working memory functioning on the dual n-back task. Overall, effects of CCT on emotion regulation were limited to reducing deployment of rumination in low positive affective states. However, we did not find beneficial effects on indicators of adaptive emotion regulation. These findings are in line with previous studies targeting maladaptive emotion regulation but suggest limited use in enhancing adaptive emotion regulation in a healthy sample. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

[Adaptation strategies faced with chronic pain].

PubMed

Bioy, Antoine

2017-05-01

Chronic pain constitutes a challenge for patients. It makes them uneasy with regard to their personality, their corporality and their life balance, and leaves long-lasting effects on their experience as a patient. The development of adaptation strategies and resources to deal with chronic pain is therefore essential. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Exposure to stressful environments - Strategy of adaptive responses

NASA Technical Reports Server (NTRS)

Farhi, Leon E.

1991-01-01

Stresses such as hypoxia, water lack, and heat exposure can produce strains in more than a single organ system, in turn stimulating the body to adapt in multiple ways. Nevertheless, a general strategy of the various adaptive responses emerges when the challenges are divided into three groups: (1) conditions that affect the supply of essential molecules, (2) stresses that prevent the body from regulating properly the output of waste products such as CO2 and heat, and (3) environments that disrupt body transport systems. Problems may arise when there is a conflict between two stresses requiring conflicting adaptive changes. An alternative to adaptation, creation of microenvironment, is often favored by the animal.

Adaptive sequential controller

DOEpatents

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

1994-01-01

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

Nonlinear adaptive formation control for a class of autonomous holonomic planetary exploration rovers

NASA Astrophysics Data System (ADS)

Ganji, Farid

This dissertation presents novel nonlinear adaptive formation controllers for a heterogeneous group of holonomic planetary exploration rovers navigating over flat terrains with unknown soil types and surface conditions. A leader-follower formation control architecture is employed. In the first part, using a point-mass model for robots and a Coulomb-viscous friction model for terrain resistance, direct adaptive control laws and a formation speed-adaptation strategy are developed for formation navigation over unknown and changing terrain in the presence of actuator saturation. On-line estimates of terrain frictional parameters compensate for unknown terrain resistance and its variations. In saturation events over difficult terrain, the formation speed is reduced based on the speed of the slowest saturated robot, using internal fleet communication and a speed-adaptation strategy, so that the formation error stays bounded and small. A formal proof for asymptotic stability of the formation system in non-saturated conditions is given. The performance of robot controllers are verified using a modular 3-robot formation simulator. Simulations show that the formation errors reduce to zero asymptotically under non-saturated conditions as is guaranteed by the theoretical proof. In the second part, the proposed adaptive control methodology is extended for formation control of a class of omnidirectional rovers with three independently-driven universal holonomic rigid wheels, where the rovers' rigid-body dynamics, drive-system electromechanical characteristics, and wheel-ground interaction mechanics are incorporated. Holonomic rovers have the ability to move simultaneously and independently in translation and rotation, rendering great maneuverability and agility, which makes them suitable for formation navigation. Novel nonlinear adaptive control laws are designed for the input voltages of the three wheel-drive motors. The motion resistance, which is due to the sinkage of rover

Adaptive Test Schemes for Control of Paratuberculosis in Dairy Cows.

PubMed

Kirkeby, Carsten; Græsbøll, Kaare; Nielsen, Søren Saxmose; Christiansen, Lasse Engbo; Toft, Nils; Halasa, Tariq

2016-01-01

Paratuberculosis is a chronic infection that in dairy cattle causes reduced milk yield, weight loss, and ultimately fatal diarrhea. Subclinical animals can excrete bacteria (Mycobacterium avium ssp. paratuberculosis, MAP) in feces and infect other animals. Farmers identify the infectious animals through a variety of test-strategies, but are challenged by the lack of perfect tests. Frequent testing increases the sensitivity but the costs of testing are a cause of concern for farmers. Here, we used a herd simulation model using milk ELISA tests to evaluate the epidemiological and economic consequences of continuously adapting the sampling interval in response to the estimated true prevalence in the herd. The key results were that the true prevalence was greatly affected by the hygiene level and to some extent by the test-frequency. Furthermore, the choice of prevalence that will be tolerated in a control scenario had a major impact on the true prevalence in the normal hygiene setting, but less so when the hygiene was poor. The net revenue is not greatly affected by the test-strategy, because of the general variation in net revenues between farms. An exception to this is the low hygiene herd, where frequent testing results in lower revenue. When we look at the probability of eradication, then it is correlated with the testing frequency and the target prevalence during the control phase. The probability of eradication is low in the low hygiene herd, and a test-and-cull strategy should probably not be the primary strategy in this herd. Based on this study we suggest that, in order to control MAP, the standard Danish dairy farm should use an adaptive strategy where a short sampling interval of three months is used when the estimated true prevalence is above 1%, and otherwise use a long sampling interval of one year.

Biometeorology - a science supporting adaptation strategies

NASA Astrophysics Data System (ADS)

Matzarakis, A.; Cegnar, T.

2010-09-01

Biometeorology as an interdisciplinary science deals with the interactions between atmospheric processes and living organisms (plants, animals and humans). If and in what way weather and climate affect the well-being of all the living creatures? This is the most important question biometeorology is answering. The International Society of Biometeorology (ISB) has built an international forum for the promotion of interdisciplinary collaboration between meteorologists, health professionals, biologists, climatologists, ecologists and other scientists. The Society acts as a community of scientists with similar interests, and fulfills an important role in providing information, expertise and advice for international organizations requiring this assistance. The ISB represents the most comprehensive organization, which brings together people with expertise in these areas. Another specific aim of the ISB is the stimulation of research. Therefore, groups of members are working on several topics organized in commissions for specific targets. The recent five commissions are working in the several fields including climate change issues. Some of examples will be presented, which have been initiated by the members of the ISB and how they can be included as a solid scientific basis to develop efficient adaptation strategies. One such example is a project combining natural and social sciences (in the fields of cooperation processes, tourism analysis and strategy, weather and climate change analysis, information and communication and knowledge transfer) in a transdisciplinary approach that includes players from tourism policy and business and which focuses on the North Sea Coast and the Black Forest. The project "Climate trends and sustainable development of tourism in coastal and mountain range regions was divided into four phases - diagnosis, assessment, strategy/design of solutions, and evaluation - where scientific subprojects and practical partners meet regularly to discuss the

Adaptive neural control of MIMO nonlinear systems with a block-triangular pure-feedback control structure.

PubMed

Chen, Zhenfeng; Ge, Shuzhi Sam; Zhang, Yun; Li, Yanan

2014-11-01

This paper presents adaptive neural tracking control for a class of uncertain multiinput-multioutput (MIMO) nonlinear systems in block-triangular form. All subsystems within these MIMO nonlinear systems are of completely nonaffine pure-feedback form and allowed to have different orders. To deal with the nonaffine appearance of the control variables, the mean value theorem is employed to transform the systems into a block-triangular strict-feedback form with control coefficients being couplings among various inputs and outputs. A systematic procedure is proposed for the design of a new singularity-free adaptive neural tracking control strategy. Such a design procedure can remove the couplings among subsystems and hence avoids the possible circular control construction problem. As a consequence, all the signals in the closed-loop system are guaranteed to be semiglobally uniformly ultimately bounded. Moreover, the outputs of the systems are ensured to converge to a small neighborhood of the desired trajectories. Simulation studies verify the theoretical findings revealed in this paper.

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

PubMed

Feng, Zhilin; Fei, Juntao

2018-01-01

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

Adaptive Management as an Effective Strategy: Interdisciplinary Perceptions for Natural Resources Management

NASA Astrophysics Data System (ADS)

Dreiss, Lindsay M.; Hessenauer, Jan-Michael; Nathan, Lucas R.; O'Connor, Kelly M.; Liberati, Marjorie R.; Kloster, Danielle P.; Barclay, Janet R.; Vokoun, Jason C.; Morzillo, Anita T.

2017-02-01

Adaptive management is a well-established approach to managing natural resources, but there is little evidence demonstrating effectiveness of adaptive management over traditional management techniques. Peer-reviewed literature attempts to draw conclusions about adaptive management effectiveness using social perceptions, but those studies are largely restricted to employees of US federal organizations. To gain a more comprehensive insight into perceived adaptive management effectiveness, this study aimed to broaden the suite of disciplines, professional affiliations, and geographic backgrounds represented by both practitioners and scholars. A questionnaire contained a series of questions concerning factors that lead to or inhibit effective management, followed by another set of questions focused on adaptive management. Using a continuum representing strategies of both adaptive management and traditional management, respondents selected those strategies that they perceived as being effective. Overall, characteristics (i.e., strategies, stakeholders, and barriers) identified by respondents as contributing to effective management closely aligned with adaptive management. Responses were correlated to the type of adaptive management experience rather than an individual's discipline, occupational, or regional affiliation. In particular, perceptions of characteristics contributing to adaptive management effectiveness varied between respondents who identified as adaptive management scholars (i.e., no implementation experience) and adaptive management practitioners. Together, these results supported two concepts that make adaptive management effective: practitioners emphasized adaptive management's value as a long-term approach and scholars noted the importance of stakeholder involvement. Even so, more communication between practitioners and scholars regarding adaptive management effectiveness could promote interdisciplinary learning and problem solving for improved

Adaptive Management as an Effective Strategy: Interdisciplinary Perceptions for Natural Resources Management.

PubMed

Dreiss, Lindsay M; Hessenauer, Jan-Michael; Nathan, Lucas R; O'Connor, Kelly M; Liberati, Marjorie R; Kloster, Danielle P; Barclay, Janet R; Vokoun, Jason C; Morzillo, Anita T

2017-02-01

Adaptive management is a well-established approach to managing natural resources, but there is little evidence demonstrating effectiveness of adaptive management over traditional management techniques. Peer-reviewed literature attempts to draw conclusions about adaptive management effectiveness using social perceptions, but those studies are largely restricted to employees of US federal organizations. To gain a more comprehensive insight into perceived adaptive management effectiveness, this study aimed to broaden the suite of disciplines, professional affiliations, and geographic backgrounds represented by both practitioners and scholars. A questionnaire contained a series of questions concerning factors that lead to or inhibit effective management, followed by another set of questions focused on adaptive management. Using a continuum representing strategies of both adaptive management and traditional management, respondents selected those strategies that they perceived as being effective. Overall, characteristics (i.e., strategies, stakeholders, and barriers) identified by respondents as contributing to effective management closely aligned with adaptive management. Responses were correlated to the type of adaptive management experience rather than an individual's discipline, occupational, or regional affiliation. In particular, perceptions of characteristics contributing to adaptive management effectiveness varied between respondents who identified as adaptive management scholars (i.e., no implementation experience) and adaptive management practitioners. Together, these results supported two concepts that make adaptive management effective: practitioners emphasized adaptive management's value as a long-term approach and scholars noted the importance of stakeholder involvement. Even so, more communication between practitioners and scholars regarding adaptive management effectiveness could promote interdisciplinary learning and problem solving for improved

Adaptive mesh strategies for the spectral element method

NASA Technical Reports Server (NTRS)

Mavriplis, Catherine

1992-01-01

An adaptive spectral method was developed for the efficient solution of time dependent partial differential equations. Adaptive mesh strategies that include resolution refinement and coarsening by three different methods are illustrated on solutions to the 1-D viscous Burger equation and the 2-D Navier-Stokes equations for driven flow in a cavity. Sharp gradients, singularities, and regions of poor resolution are resolved optimally as they develop in time using error estimators which indicate the choice of refinement to be used. The adaptive formulation presents significant increases in efficiency, flexibility, and general capabilities for high order spectral methods.

Coping and adaptive strategies of traumatic brain injury survivors and primary caregivers.

PubMed

Adams, Deana; Dahdah, Marie

2016-06-27

Qualitative research methods allowed the investigator to contribute to the development of new theories and to examine change in processes over time, which added rich detail to existing knowledge of the use of coping and adaptive strategies by traumatic brain injury survivors and their primary caregivers (Ponsford, Sloan, & Snow, 2013). The advantages of phenomenological study were that it allows flexibility to explore and understand meanings attached by people to well-studied concepts such as coping, resiliency, and adaptation or compensation. Phenomenological study was sensitive to contextual factors. It also permitted the study of in-depth dynamics of coping and adaptive strategies of TBI survivors and primary caregivers, while understanding the social and psychological implications of the phenomenon. To explore the needs and deficits of adult traumatic brain injury (TBI) survivors and primary caregivers; and to identify their self-initiated coping and adaptive strategies. Significant to this study was the development of coping and adaptive strategies by the participants after their discharge from inpatient and rehabilitation treatment. The compensatory skills taught in treatment settings did not transfer to the home environment. Therefore, these strategies developed independently from previous treatment recommendations contributed to the development of theory related to rehabilitation and counseling. Distinctive to this study was the similarity of coping and adaptive strategies developed from both mild and severe traumatic brain injury survivors. This study consisted of eleven with TBI and six primary caregivers (N = 17), who participated in a series of semi-structured interviews aimed at discovering the coping and adaptive strategies utilized in dealing with the effects of brain injury. A Qualitative Phenomenological design was employed. Patience and understanding, support, and professional help were identified by TBI survivors and caregivers as being their

Mean deviation coupling synchronous control for multiple motors via second-order adaptive sliding mode control.

PubMed

Li, Lebao; Sun, Lingling; Zhang, Shengzhou

2016-05-01

A new mean deviation coupling synchronization control strategy is developed for multiple motor control systems, which can guarantee the synchronization performance of multiple motor control systems and reduce complexity of the control structure with the increasing number of motors. The mean deviation coupling synchronization control architecture combining second-order adaptive sliding mode control (SOASMC) approach is proposed, which can improve synchronization control precision of multiple motor control systems and make speed tracking errors, mean speed errors of each motor and speed synchronization errors converge to zero rapidly. The proposed control scheme is robustness to parameter variations and random external disturbances and can alleviate the chattering phenomena. Moreover, an adaptive law is employed to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. Performance comparisons with master-slave control, relative coupling control, ring coupling control, conventional PI control and SMC are investigated on a four-motor synchronization control system. Extensive comparative results are given to shown the good performance of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation.

PubMed

Deng, Wenxiang; Yao, Jianyong; Ma, Dawei

2017-09-01

This paper addresses the high performance motion control of hydraulic actuators with parametric uncertainties, unmodeled disturbances and unknown valve dead-zone. By constructing a smooth dead-zone inverse, a robust adaptive controller is proposed via backstepping method, in which adaptive law is synthesized to deal with parametric uncertainties and a continuous nonlinear robust control law to suppress unmodeled disturbances. Since the unknown dead-zone parameters can be estimated by adaptive law and then the effect of dead-zone can be compensated effectively via inverse operation, improved tracking performance can be expected. In addition, the disturbance upper bounds can also be updated online by adaptive laws, which increases the controller operability in practice. The Lyapunov based stability analysis shows that excellent asymptotic output tracking with zero steady-state error can be achieved by the developed controller even in the presence of unmodeled disturbance and unknown valve dead-zone. Finally, the proposed control strategy is experimentally tested on a servovalve controlled hydraulic actuation system subjected to an artificial valve dead-zone. Comparative experimental results are obtained to illustrate the effectiveness of the proposed control scheme. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Sleep Strategies of Night-Shift Nurses on Days Off: Which Ones are Most Adaptive?

PubMed

Petrov, Megan E; Clark, C Brendan; Molzof, Hylton E; Johnson, Russell L; Cropsey, Karen L; Gamble, Karen L

2014-01-01

To determine the off-shift sleep strategies of bi-ethnic night-shift nurses, the relationship between these sleep strategies and adaptation to shift work, and identify the participant-level characteristics associated with a given sleep strategy. African-American and non-Hispanic White female, night-shift nurses from an academic hospital were recruited to complete a survey on sleep-wake patterns (n = 213). Participants completed the standard shiftwork index and the biological clocks questionnaire to determine sleep strategies and adaptation to night-shift work. In addition, chronotype was determined quantitatively with a modified version of the Munich ChronoType Questionnaire. Most participants worked ~3 consecutive 12-h night-shifts followed by several days off. Five sleep strategies used on days off were identified: (a) night stay, (b) nap proxy, (c) switch sleeper, (d) no sleep, and (e) incomplete switcher. Nap proxy and no sleep types were associated with poorer adaptation to night-shift work. The switch sleeper and incomplete switcher types were identified as more adaptive strategies that were associated with less sleep disturbance, a later chronotype, and less cardiovascular problems. Behavioral sleep strategies are related to adaptation to a typical night-shift schedule among hospital nurses. Nurses are crucial to the safety and well-being of their patients. Therefore, adoption of more adaptive sleep strategies may reduce sleep/wake dysregulation in this population, and improve cardiovascular outcomes.

Vulnerability of maize production under future climate change: possible adaptation strategies.

PubMed

Bannayan, Mohammad; Paymard, Parisa; Ashraf, Batool

2016-10-01

Climate change can affect the productivity and geographic distribution of crops. Therefore, evaluation of adaptive management options is crucial in dealing with negative impacts of climate change. The objectives of this study were to simulate the impacts of climate change on maize production in the north-east of Iran. Moreover, vulnerability index which indicated that how much of the crop yield loss is related to the drought was computed for each location to identify where adaptation and mitigation strategies are effective. Different sowing dates were also applied as an adaptation approach to decrease the negative impacts of climate change in study area. The results showed that the maize yield would decline during the 21st century from -2.6% to -82% at all study locations in comparison with the baseline. The result of vulnerability index also indicated that using the adaptation strategies could be effective in all of the study areas. Using different sowing dates as an adaptation approach showed that delaying the sowing date will be advantageous in order to obtain higher yield in all study locations in future. This study provided insight regarding the climate change impacts on maize production and the efficacy of adaptation strategies. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Adaptive strategies to climate change in Southern Malawi

NASA Astrophysics Data System (ADS)

Chidanti-Malunga, J.

Climate change poses a big challenge to rural livelihoods in the Shire Valley area of Southern Malawi, where communities have depended almost entirely on rain-fed agriculture for generations. The Shire Valley area comprises of low-altitude dambo areas and uplands which have been the main agricultural areas. Since early to mid 1980s, the uplands have experienced prolonged droughts and poor rainfall distribution, while the dambos have experienced recurrent seasonal floods. This study assessed some of the adaptive strategies exercised by small-scale rural farmers in response to climate change in the Shire Valley. The methodology used in collecting information includes group discussions, household surveys in the area, secondary data, and field observations. The results show that small-scale rural farmers exercise a number of adaptive strategies in response to climate change. These adaptive strategies include: increased use of water resources for small-scale irrigation or wetland farming, mostly using simple delivery techniques; increased management of residual moisture; and increased alternative sources of income such as fishing and crop diversity. It was also observed that government promoted the use of portable motorized pumps for small-scale irrigation in order to mitigate the effects of climate change. However, these external interventions were not fully adopted; instead the farmers preferred local interventions which mostly had indigenous elements.

Adaptive Strategies, Gender Ideology, and Work-Family Balance among Dutch Dual Earners

ERIC Educational Resources Information Center

Wierda-Boer, Hilde H.; Gerris, Jan R. M.; Vermulst, Ad A.

2008-01-01

Using questionnaire data on 149 Dutch dual-earner couples with young children participating in the European Famwork study, we examine how adaptive strategies and gender ideology relate to parents' perceived success in balancing work and family. Path analysis indicates that some adaptive strategies may harm individuals' work-family balance,…

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

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.

Public authority control strategy for opinion evolution in social networks

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Public authority control strategy for opinion evolution in social networks.

PubMed

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

2016-08-01

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

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

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

2010-01-01

This paper is devoted to the design and analysis of a predictor-based model reference adaptive control. Stable adaptive laws are derived using Lyapunov framework. The proposed architecture is compared with the now classical model reference adaptive control. A simulation example is presented in which numerical evidence indicates that the proposed controller yields improved transient characteristics.

Assessment of the effectiveness of participatory developed adaptation strategies for HCMC

NASA Astrophysics Data System (ADS)

Lasage, R.; Veldkamp, T. I. E.; de Moel, H.; Van, T. C.; Phi, H. L.; Vellinga, P.; Aerts, J. C. J. H.

2014-01-01

Coastal cities are vulnerable to flooding, and flood risk to coastal cities will increase due to sea-level rise. Moreover, especially Asian cities are subject to considerable population growth and associated urban developments, increasing this risk even more. Empirical data on vulnerability and the cost and benefits of flood risk reducing measures are therefore paramount for sustainable development of these cities. This paper presents an approach to explore the impacts of sea level rise and socio-economic developments on flood risk for the flood prone District 4 in Ho Chi Minh City, Vietnam, and to develop and evaluate the effects of different adaptation strategies (new levees, dry- and wet flood proofing of buildings). A flood damage model was developed to simulate current and future flood risk using the results from a household survey to establish stage-damage curves for residential buildings. the model has been used to assess the effects of several participatory developed adaptation strategies to reduce flood risk, expressed in Expected Annual Damage (EAD). Adaptation strategies were evaluated assuming combinations of both sea level scenarios and land use scenarios. Together with information on costs of these strategies, we calculated the benefit-cost ratio and net present value for the adaptation strategies until 2100, taking into account depreciation rates of 2.5% and 5%. The results of this modeling study indicate that the current flood risk in District 4 is 0.31 million USD yr-1, increasing up to 0.78 million USD yr-1 in 2100. The net present value and benefit-cost ratios using a discount rate of 5% range from USD -107 to -1.5 million, and from 0.086 to 0.796 for the different strategies. Using a discount rate of 2.5% leads to an increase in both net present value and benefit cost ratio. The adaptation strategies wet proofing and dry proofing generate the best results using these economic indicators. The information on different strategies will be used by

Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

PubMed

Tong, Shaocheng; Li, Yongming

2017-02-01

This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

Sleep Strategies of Night-Shift Nurses on Days Off: Which Ones are Most Adaptive?

PubMed Central

Petrov, Megan E.; Clark, C. Brendan; Molzof, Hylton E.; Johnson, Russell L.; Cropsey, Karen L.; Gamble, Karen L.

2014-01-01

Objectives: To determine the off-shift sleep strategies of bi-ethnic night-shift nurses, the relationship between these sleep strategies and adaptation to shift work, and identify the participant-level characteristics associated with a given sleep strategy. Methods: African-American and non-Hispanic White female, night-shift nurses from an academic hospital were recruited to complete a survey on sleep–wake patterns (n = 213). Participants completed the standard shiftwork index and the biological clocks questionnaire to determine sleep strategies and adaptation to night-shift work. In addition, chronotype was determined quantitatively with a modified version of the Munich ChronoType Questionnaire. Most participants worked ~3 consecutive 12-h night-shifts followed by several days off. Results: Five sleep strategies used on days off were identified: (a) night stay, (b) nap proxy, (c) switch sleeper, (d) no sleep, and (e) incomplete switcher. Nap proxy and no sleep types were associated with poorer adaptation to night-shift work. The switch sleeper and incomplete switcher types were identified as more adaptive strategies that were associated with less sleep disturbance, a later chronotype, and less cardiovascular problems. Conclusion: Behavioral sleep strategies are related to adaptation to a typical night-shift schedule among hospital nurses. Nurses are crucial to the safety and well-being of their patients. Therefore, adoption of more adaptive sleep strategies may reduce sleep/wake dysregulation in this population, and improve cardiovascular outcomes. PMID:25566182

Adaptive fuzzy predictive sliding control of uncertain nonlinear systems with bound-known input delay.

PubMed

Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan

2015-11-01

In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Strategies of Mesenchymal Invasion of Patient-derived Brain Tumors: Microenvironmental Adaptation.

PubMed

Cha, Junghwa; Kang, Seok-Gu; Kim, Pilnam

2016-04-25

The high mortality in glioblastoma multiforme (GBM) patients is primarily caused by extensive infiltration into adjacent tissue and subsequent rapid recurrence. There are no clear therapeutic strategies that target the infiltrative subpopulation of GBM mass. Using mesenchymal mode of invasion, the GBM is known to widely infiltrate by interacting with various unique components within brain microenvironment such as hyaluronic acid (HA)-rich matrix and white matter tracts. However, it is unclear how these GBM microenvironments influence the strategies of mesenchymal invasion. We hypothesize that GBM has different strategies to facilitate such invasion through adaptation to their local microenvironment. Using our in vitro biomimetic microenvironment platform for three-dimensional GBM tumorspheres (TSs), we found that the strategies of GBM invasion were predominantly regulated by the HA-rich ECM microenvironment, showing marked phenotypic changes in the presence of HA, which were mainly mediated by HA synthase (HAS). Interestingly, after inhibition of the HAS gene, GBM switched their invasion strategies to a focal adhesion (FA)-mediated invasion. These results demonstrate that the microenvironmental adaptation allowed a flexible invasion strategy for GBM. Using our model, we suggest a new inhibitory pathway for targeting infiltrative GBM and propose an importance of multi-target therapy for GBM, which underwent microenvironmental adaptation.

Managing work and family: Do control strategies help?

PubMed

Versey, H Shellae

2015-11-01

How can we effectively manage competing obligations from work and family without becoming overwhelmed? This question inspires the current study by examining control strategies that may facilitate better work-life balance, with a specific focus on the role of lowered aspirations and positive reappraisals, attitudes that underlie adaptive coping behaviors. Data from the Midlife in the United States Survey (MIDUS II) were used to explore the relationship between negative spillover, control strategies, and well-being among full-time working men and women (N = 2,091). In this nationally representative sample, findings indicate that while positive reappraisals function as a protective buffer, lowering aspirations exacerbate the relationship between work-family spillover and well-being, with moderating effects stronger among women. This study extends prior research tying work-life conflict to health and mental health, and suggests further investigation is needed to consider types of resources that may be effective coping strategies in balancing work and family. (c) 2015 APA, all rights reserved).

Criticality of Adaptive Control Dynamics

NASA Astrophysics Data System (ADS)

Patzelt, Felix; Pawelzik, Klaus

2011-12-01

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

Adaptive Strategy Selection in Decision Making.

DTIC Science & Technology

1986-07-31

information processing capabilities of a decision maker, given any " reasonable " time limit for making the decision. If use of a more normative rule...DECISION MAKING JOHN W. PAYNE DTIC DUKE UNIVERSITY L.CT E AUG 13 JAMES R. BETTMAN DUKE. UNIVERSITY ERIC J. JOHNSON CARNEGIE-MELLON UNIVERSITY...REPORT & PERIOD COVERED ADAPTIVE STRATEGY SELECTION IN DECISION MAKING Research 6. PERFORMING ORO. REPORT NUMSER 7. AUTNORfe) e. CONTRACT ON GRANT

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics.

PubMed

Li, Yongming; Sui, Shuai; Tong, Shaocheng

2017-02-01

This paper deals with the problem of adaptive fuzzy output feedback control for a class of stochastic nonlinear switched systems. The controlled system in this paper possesses unmeasured states, completely unknown nonlinear system functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on the switching signal is constructed to tackle the unmeasured states. Fuzzy logic systems are employed to identify the completely unknown nonlinear system functions. Based on the common Lyapunov stability theory and stochastic small-gain theorem, a new robust adaptive fuzzy backstepping stabilization control strategy is developed. The stability of the closed-loop system on input-state-practically stable in probability is proved. The simulation results are given to verify the efficiency of the proposed fuzzy adaptive control scheme.

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

An adaptive Cartesian control scheme for manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

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.

High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter

PubMed Central

Xu, Dan; Zhou, Huan; Bai, Anning; Lu, Wei

2017-01-01

This paper presents an adaption of the fractional order terminal sliding mode control (AFTSMC) strategy for DC-DC Buck converter. The following strategy aims to design a novel nonlinear sliding surface function, with a double closed-loop structure of voltage and current. This strategy is a fusion of two characteristics: terminal sliding mode control (TSMC) and fractional order calculation (FOC). In addition, the influence of “the controller parameters” on the “performance of double closed-loop system” is investigated. It is observed that the value of terminal power has to be chosen to make a compromise between start-up and transient response of the converter. Therefore the AFTSMC strategy chooses the value of the terminal power adaptively, and this strategy can lead to the appropriate number of fractional order as well. Furthermore, through the fractional order analysis, the system can reach the sliding mode surface in a finite time. And the theoretical considerations are verified by numerical simulation. The performance of the AFTSMC and TSMC strategies is tested by computer simulations. And the comparison simulation results show that the AFTSMC exhibits a considerable improvement in terms of a faster output voltage response during load changes. Moreover, AFTSMC obtains a faster dynamical response, smaller steady-state error rate and lower overshoot. PMID:29084255

High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter.

PubMed

Wang, Jianlin; Xu, Dan; Zhou, Huan; Bai, Anning; Lu, Wei

2017-01-01

This paper presents an adaption of the fractional order terminal sliding mode control (AFTSMC) strategy for DC-DC Buck converter. The following strategy aims to design a novel nonlinear sliding surface function, with a double closed-loop structure of voltage and current. This strategy is a fusion of two characteristics: terminal sliding mode control (TSMC) and fractional order calculation (FOC). In addition, the influence of "the controller parameters" on the "performance of double closed-loop system" is investigated. It is observed that the value of terminal power has to be chosen to make a compromise between start-up and transient response of the converter. Therefore the AFTSMC strategy chooses the value of the terminal power adaptively, and this strategy can lead to the appropriate number of fractional order as well. Furthermore, through the fractional order analysis, the system can reach the sliding mode surface in a finite time. And the theoretical considerations are verified by numerical simulation. The performance of the AFTSMC and TSMC strategies is tested by computer simulations. And the comparison simulation results show that the AFTSMC exhibits a considerable improvement in terms of a faster output voltage response during load changes. Moreover, AFTSMC obtains a faster dynamical response, smaller steady-state error rate and lower overshoot.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

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

Mechanisms in adaptive feedback control: photoisomerization in a liquid.

PubMed

Hoki, Kunihito; Brumer, Paul

2005-10-14

The underlying mechanism for Adaptive Feedback Control in the experimental photoisomerization of 3,3'-diethyl-2,2'-thiacyanine iodide (NK88) in methanol is exposed theoretically. With given laboratory limitations on laser output, the complicated electric fields are shown to achieve their targets in qualitatively simple ways. Further, control over the cis population without laser limitations reveals an incoherent pump-dump scenario as the optimal isomerization strategy. In neither case are there substantial contributions from quantum multiple-path interference or from nuclear wave packet coherence. Environmentally induced decoherence is shown to justify the use of a simplified theoretical model.

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS

PubMed Central

Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system. PMID:29702696

Adaptive fractional order sliding mode control for Boost converter in the Battery/Supercapacitor HESS.

PubMed

Wang, Jianlin; Xu, Dan; Zhou, Huan; Zhou, Tao

2018-01-01

In this paper, an adaptive fractional order sliding mode control (AFSMC) scheme is designed for the current tracking control of the Boost-type converter in a Battery/Supercapacitor hybrid energy storage system (HESS). In order to stabilize the current, the adaptation rules based on state-observer and Lyapunov function are being designed. A fractional order sliding surface function is defined based on the tracking current error and adaptive rules. Furthermore, through fractional order analysis, the stability of the fractional order control system is proven, and the value of the fractional order (λ) is being investigated. In addition, the effectiveness of the proposed AFSMC strategy is being verified by numerical simulations. The advantages of good transient response and robustness to uncertainty are being indicated by this design, when compared with a conventional integer order sliding mode control system.

Adaptive strategies for materials design using uncertainties

DOE PAGES

Balachandran, Prasanna V.; Xue, Dezhen; Theiler, James; ...

2016-01-21

Here, we compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. The design strategies are decomposed into an iterative loop with two main steps: machine learning is used to train a regressor that predicts elastic properties in terms of elementary orbital radii of the individual components of the materials; and a selector uses these predictions and their uncertainties to choose the next material to investigate. The ultimate goal is to obtain a material withmore » desired elastic properties in as few iterations as possible. We examine how the choice of data set size, regressor and selector impact the design. We find that selectors that use information about the prediction uncertainty outperform those that don’t. Our work is a step in illustrating how adaptive design tools can guide the search for new materials with desired properties.« less

Adaptive strategies for materials design using uncertainties

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

Balachandran, Prasanna V.; Xue, Dezhen; Theiler, James

Here, we compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. The design strategies are decomposed into an iterative loop with two main steps: machine learning is used to train a regressor that predicts elastic properties in terms of elementary orbital radii of the individual components of the materials; and a selector uses these predictions and their uncertainties to choose the next material to investigate. The ultimate goal is to obtain a material withmore » desired elastic properties in as few iterations as possible. We examine how the choice of data set size, regressor and selector impact the design. We find that selectors that use information about the prediction uncertainty outperform those that don’t. Our work is a step in illustrating how adaptive design tools can guide the search for new materials with desired properties.« less

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Adaptive Control for Buck Power Converter Using Fixed Point Inducting Control and Zero Average Dynamics Strategies

NASA Astrophysics Data System (ADS)

Hoyos Velasco, Fredy Edimer; García, Nicolás Toro; Garcés Gómez, Yeison Alberto

In this paper, the output voltage of a buck power converter is controlled by means of a quasi-sliding scheme. The Fixed Point Inducting Control (FPIC) technique is used for the control design, based on the Zero Average Dynamics (ZAD) strategy, including load estimation by means of the Least Mean Squares (LMS) method. The control scheme is tested in a Rapid Control Prototyping (RCP) system based on Digital Signal Processing (DSP) for dSPACE platform. The closed loop system shows adequate performance. The experimental and simulation results match. The main contribution of this paper is to introduce the load estimator by means of LMS, to make ZAD and FPIC control feasible in load variation conditions. In addition, comparison results for controlled buck converter with SMC, PID and ZAD-FPIC control techniques are shown.

Statistical Physics for Adaptive Distributed Control

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2005-01-01

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

Flight Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

Adaptive Flight Control Research at NASA

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2008-01-01

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

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Modeling and simulation of permanent magnet synchronous motor based on neural network control strategy

NASA Astrophysics Data System (ADS)

Luo, Bingyang; Chi, Shangjie; Fang, Man; Li, Mengchao

2017-03-01

Permanent magnet synchronous motor is used widely in industry, the performance requirements wouldn't be met by adopting traditional PID control in some of the occasions with high requirements. In this paper, a hybrid control strategy - nonlinear neural network PID and traditional PID parallel control are adopted. The high stability and reliability of traditional PID was combined with the strong adaptive ability and robustness of neural network. The permanent magnet synchronous motor will get better control performance when switch different working modes according to different controlled object conditions. As the results showed, the speed response adopting the composite control strategy in this paper was faster than the single control strategy. And in the case of sudden disturbance, the recovery time adopting the composite control strategy designed in this paper was shorter, the recovery ability and the robustness were stronger.

Transitions in optimal adaptive strategies for populations in fluctuating environments

NASA Astrophysics Data System (ADS)

Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.

2017-09-01

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.

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.

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

PubMed

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

2012-11-10

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

Adaptive nonlinear polynomial neural networks for control of boundary layer/structural interaction

NASA Technical Reports Server (NTRS)

Parker, B. Eugene, Jr.; Cellucci, Richard L.; Abbott, Dean W.; Barron, Roger L.; Jordan, Paul R., III; Poor, H. Vincent

1993-01-01

The acoustic pressures developed in a boundary layer can interact with an aircraft panel to induce significant vibration in the panel. Such vibration is undesirable due to the aerodynamic drag and structure-borne cabin noises that result. The overall objective of this work is to develop effective and practical feedback control strategies for actively reducing this flow-induced structural vibration. This report describes the results of initial evaluations using polynomial, neural network-based, feedback control to reduce flow induced vibration in aircraft panels due to turbulent boundary layer/structural interaction. Computer simulations are used to develop and analyze feedback control strategies to reduce vibration in a beam as a first step. The key differences between this work and that going on elsewhere are as follows: that turbulent and transitional boundary layers represent broadband excitation and thus present a more complex stochastic control scenario than that of narrow band (e.g., laminar boundary layer) excitation; and secondly, that the proposed controller structures are adaptive nonlinear infinite impulse response (IIR) polynomial neural network, as opposed to the traditional adaptive linear finite impulse response (FIR) filters used in most studies to date. The controllers implemented in this study achieved vibration attenuation of 27 to 60 dB depending on the type of boundary layer established by laminar, turbulent, and intermittent laminar-to-turbulent transitional flows. Application of multi-input, multi-output, adaptive, nonlinear feedback control of vibration in aircraft panels based on polynomial neural networks appears to be feasible today. Plans are outlined for Phase 2 of this study, which will include extending the theoretical investigation conducted in Phase 2 and verifying the results in a series of laboratory experiments involving both bum and plate models.

A New Method for the Adaptive Control of Vortex-Wall Interactions

NASA Technical Reports Server (NTRS)

Koumoutsakos, P.

1996-01-01

The control of vortical flows is gaining significance in the design of aeronautical and marine structures. While passive devices have been used effectively in the past, active control strategies have the potential of allowing a leap in the performance of future configurations. The efficiency of control schemes is strongly dependent on the development of accurate flow models that can be devised using information that is available not only from numerical solutions of the governing Navier-Stokes equations but also can be measured experimentally. In that context it is desirable to construct adaptive control schemes using information that can be measured at the wall.

Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: adaptation of muscle activation and movement frequency.

PubMed

Aguirre-Ollinger, Gabriel

2015-01-01

In this article, we analyze a novel strategy for assisting the lower extremities based on adaptive frequency oscillators. Our aim is to use the control algorithm presented here as a building block for the control of powered lower-limb exoskeletons. The algorithm assists cyclic movements of the human extremities by synchronizing actuator torques with the estimated net torque exerted by the muscles. Synchronization is produced by a nonlinear dynamical system combining an adaptive frequency oscillator with a form of adaptive Fourier analysis. The system extracts, in real time, the fundamental frequency component of the net muscle torque acting on a specific joint. Said component, nearly sinusoidal in shape, is the basis for the assistive torque waveform delivered by the exoskeleton. The action of the exoskeleton can be interpreted as a virtual reduction in the mechanical impedance of the leg. We studied the ability of human subjects to adapt their muscle activation to the assistive torque. Ten subjects swung their extended leg while coupled to a stationary hip joint exoskeleton. The experiment yielded a significant decrease, with respect to unassisted movement, of the activation levels of an agonist/antagonist pair of muscles controlling the hip joint's motion, which suggests the exoskeleton control has potential for assisting human gait. A moderate increase in swing frequency was observed as well. We theorize that the increase in frequency can be explained by the impedance model of the assisted leg. Per this model, subjects adjust their swing frequency in order to control the amount of reduction in net muscle torque. © IMechE 2015.

A new RISE-based adaptive control of PKMs: design, stability analysis and experiments

NASA Astrophysics Data System (ADS)

Bennehar, M.; Chemori, A.; Bouri, M.; Jenni, L. F.; Pierrot, F.

2018-03-01

This paper deals with the development of a new adaptive control scheme for parallel kinematic manipulators (PKMs) based on Rrbust integral of the sign of the error (RISE) control theory. Original RISE control law is only based on state feedback and does not take advantage of the modelled dynamics of the manipulator. Consequently, the overall performance of the resulting closed-loop system may be poor compared to modern advanced model-based control strategies. We propose in this work to extend RISE by including the nonlinear dynamics of the PKM in the control loop to improve its overall performance. More precisely, we augment original RISE control scheme with a model-based adaptive control term to account for the inherent nonlinearities in the closed-loop system. To demonstrate the relevance of the proposed controller, real-time experiments are conducted on the Delta robot, a three-degree-of-freedom (3-DOF) PKM.

Synchronization of coupled stochastic complex-valued dynamical networks with time-varying delays via aperiodically intermittent adaptive control

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Jin, Wei; Su, Huan

2018-04-01

This paper deals with the synchronization problem of a class of coupled stochastic complex-valued drive-response networks with time-varying delays via aperiodically intermittent adaptive control. Different from the previous works, the intermittent control is aperiodic and adaptive, and the restrictions on the control width and time delay are removed, which lead to a larger application scope for this control strategy. Then, based on the Lyapunov method and Kirchhoff's Matrix Tree Theorem as well as differential inequality techniques, several novel synchronization conditions are derived for the considered model. Specially, impulsive control is also considered, which can be seen as a special case of the aperiodically intermittent control when the control width tends to zero. And the corresponding synchronization criteria are given as well. As an application of the theoretical results, a class of stochastic complex-valued coupled oscillators with time-varying delays is studied, and the numerical simulations are also given to demonstrate the effectiveness of the control strategies.

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

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

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

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

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.

Intelligent fault recognition strategy based on adaptive optimized multiple centers

NASA Astrophysics Data System (ADS)

Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

2018-06-01

For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

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.

Direct adaptive control of manipulators in Cartesian space

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies.

PubMed

Shehata, Ahmed W; Scheme, Erik J; Sensinger, Jonathon W

2018-05-01

On-going developments in myoelectric prosthesis control have provided prosthesis users with an assortment of control strategies that vary in reliability and performance. Many studies have focused on improving performance by providing feedback to the user but have overlooked the effect of this feedback on internal model development, which is key to improve long-term performance. In this paper, the strength of internal models developed for two commonly used myoelectric control strategies: raw control with raw feedback (using a regression-based approach) and filtered control with filtered feedback (using a classifier-based approach), were evaluated using two psychometric measures: trial-by-trial adaptation and just-noticeable difference. The performance of both strategies was also evaluated using Schmidt's style target acquisition task. Results obtained from 24 able-bodied subjects showed that although filtered control with filtered feedback had better short-term performance in path efficiency ( ), raw control with raw feedback resulted in stronger internal model development ( ), which may lead to better long-term performance. Despite inherent noise in the control signals of the regression controller, these findings suggest that rich feedback associated with regression control may be used to improve human understanding of the myoelectric control system.

Flight Test Approach to Adaptive Control Research

NASA Technical Reports Server (NTRS)

Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

2011-01-01

The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

Adaptive-passive vibration control systems for industrial applications

NASA Astrophysics Data System (ADS)

Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.

2015-04-01

Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.

Exposure to Stressful Environments: Strategy of Adaptive Responses

NASA Technical Reports Server (NTRS)

Farhi, Leon E.

1991-01-01

Any new natural environment may generate a number of stresses (such as hypoxia, water lack, and heat exposure), each of which can produce strains in more than a single organ system. Every strain may in turn stimulate the body to adapt in multiple ways. Nevertheless, a general strategy of the various adaptive responses emerges when the challenges are divided into three groups. The first category includes conditions that affect the supply of essential molecules, while the second is made up by those stresses that prevent the body from regulating properly the output of waste products, such as CO2 and heat. In both classes, there is a small number of responses, similar in principle, regardless of the specific situation. The third unit is created by environments that disrupt body transport systems. Problems may arise when there is a conflict between two stresses requiring conflicting adaptive changes. An alternative to adaptation, creation of micro-environment, is often favored by the animal.

An adaptation strategy of sandland peasants in Yogyakarta toward climate change

NASA Astrophysics Data System (ADS)

Rusdiyana, E.; Suminah

2018-03-01

This study aims to explore and describe the adaptation strategies of sandland peasants toward climate change. Qualitative research method was employed and the data were collected through observation. In addition, the recording of the data, interview and the validity of data were determined by triangulation of sources. The results of the research showed that the adaptation strategies of sandland peasants toward climate change were; (1) the adjustment of crop varieties, (2) the utilization of productive crops as wind breaking, and (3) the irrigation system using “sumur panthek”.

Adaptive Fuzzy Control for Nonstrict Feedback Systems With Unmodeled Dynamics and Fuzzy Dead Zone via Output Feedback.

PubMed

Wang, Lijie; Li, Hongyi; Zhou, Qi; Lu, Renquan

2017-09-01

This paper investigates the problem of observer-based adaptive fuzzy control for a category of nonstrict feedback systems subject to both unmodeled dynamics and fuzzy dead zone. Through constructing a fuzzy state observer and introducing a center of gravity method, unmeasurable states are estimated and the fuzzy dead zone is defuzzified, respectively. By employing fuzzy logic systems to identify the unknown functions. And combining small-gain approach with adaptive backstepping control technique, a novel adaptive fuzzy output feedback control strategy is developed, which ensures that all signals involved are semi-globally uniformly bounded. Simulation results are given to demonstrate the effectiveness of the presented method.

Research in digital adaptive flight controllers

NASA Technical Reports Server (NTRS)

Kaufman, H.

1976-01-01

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

Climate change adaptation strategies and mitigation policies

NASA Astrophysics Data System (ADS)

García Fernández, Cristina

2015-04-01

The pace of climate change and the consequent warming of the Earth's surface is increasing vulnerability and decreasing adaptive capacity. Achieving a successful adaptation depends on the development of technology, institutional organization, financing availability and the exchange of information. Populations living in arid and semi-arid zones, low-lying coastal areas, land with water shortages or at risk of overflow or small islands are particularly vulnerable to climate change. Due to increasing population density in sensitive areas, some regions have become more vulnerable to events such as storms, floods and droughts, like the river basins and coastal plains. Human activities have fragmented and increased the vulnerability of ecosystems, which limit both, their natural adaptation and the effectiveness of the measures adopted. Adaptation means to carry out the necessary modifications for society to adapt to new climatic conditions in order to reduce their vulnerability to climate change. Adaptive capacity is the ability of a system to adjust to climate change (including climate variability and extremes) and to moderate potential damages, to take advantage of opportunities or face the consequences. Adaptation reduces the adverse impacts of climate change and enhance beneficial impacts, but will not prevent substantial cost that are produced by all damages. The performances require adaptation actions. These are defined and implemented at national, regional or local levels since many of the impacts and vulnerabilities depend on the particular economic, geographic and social circumstances of each country or region. We will present some adaptation strategies at national and local level and revise some cases of its implementation in several vulnerable areas. However, adaptation to climate change must be closely related to mitigation policies because the degree of change planned in different climatic variables is a function of the concentration levels that are achieved

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

PubMed Central

Dawson, Ree; Lavori, Philip W.

2009-01-01

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

Cycles of adaptive strategies over the life course.

PubMed

Cooper, Margaret; Bigby, Christine

2014-01-01

An increasing number of Australia's ageing population are aging with long-term physical impairments. This study explored the life experiences of this group using a qualitative approach. In-depth interviews were conducted with 10 disabled Victorians, aged between 51 and 84 years, and an inductive thematic analysis undertaken. A relationship was found between the adaptive strategies that participants developed as they moved through life phases and the impairment stages. The implications of the emergence of a cyclical process of adaptation across the life course. and particularly in respect of aging, delivery of aged-care services and social workers in this sector are discussed.

Adaptive NN Control Using Integral Barrier Lyapunov Functionals for Uncertain Nonlinear Block-Triangular Constraint Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2017-11-01

A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs. The novel integral barrier Lyapunov functionals (BLFs) are employed to overcome the violation of the full state constraints. The proposed strategy can not only guarantee the boundedness of the closed-loop system and the outputs are driven to follow the reference signals, but also can ensure all the states to remain in the predefined compact sets. Moreover, the transformed constraints on the errors are used in the previous BLF, and accordingly it is required to determine clearly the bounds of the virtual controllers. Thus, it can relax the conservative limitations in the traditional BLF-based controls for the full state constraints. This conservatism can be solved in this paper and it is for the first time to control this class of MIMO systems with the full state constraints. The performance of the proposed control strategy can be verified through a simulation example.

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

PubMed

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

2017-07-01

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

An adaptive deep Q-learning strategy for handwritten digit recognition.

PubMed

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predictor-Based Model Reference Adaptive Control

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

A Methodology for Investigating Adaptive Postural Control

NASA Technical Reports Server (NTRS)

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

1999-01-01

overt goals. It follows that an essential characteristic of postural behavior is the effective maintenance of the orientation and stability of the sensory and motor "platforms" (e.g., head or shoulders) over variations in the human, the environment and the task. This general skill suggests that individuals should be sensitive to the functional consequences of body configuration and stability. In other words, individuals should perceive the relation between configuration, stability, and performance so that they can adaptively control their interaction with the surroundings. Human-environment interactions constitute robust systems in that individuals can maintain the stability of such interactions over uncertainty about and variations in the dynamics of the interaction. Robust interactions allow individuals to adopt orientations and configurations that are not optimal with respect to purely energetic criteria. Individuals can tolerate variation in postural states, and such variation can serve an important function in adaptive systems. Postural variability generates stimulation which is "textured" by the dynamics of the human-environment system. The texture or structure in stimulation provides information about variation in dynamics, and such information can be sufficient to guide adaption in control strategies. Our method were designed to measure informative patterns of movement variability.

Stable adaptive PI control for permanent magnet synchronous motor drive based on improved JITL technique.

PubMed

Zheng, Shiqi; Tang, Xiaoqi; Song, Bao; Lu, Shaowu; Ye, Bosheng

2013-07-01

In this paper, a stable adaptive PI control strategy based on the improved just-in-time learning (IJITL) technique is proposed for permanent magnet synchronous motor (PMSM) drive. Firstly, the traditional JITL technique is improved. The new IJITL technique has less computational burden and is more suitable for online identification of the PMSM drive system which is highly real-time compared to traditional JITL. In this way, the PMSM drive system is identified by IJITL technique, which provides information to an adaptive PI controller. Secondly, the adaptive PI controller is designed in discrete time domain which is composed of a PI controller and a supervisory controller. The PI controller is capable of automatically online tuning the control gains based on the gradient descent method and the supervisory controller is developed to eliminate the effect of the approximation error introduced by the PI controller upon the system stability in the Lyapunov sense. Finally, experimental results on the PMSM drive system show accurate identification and favorable tracking performance. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Possible impacts of sea level rise on disease transmission and potential adaptation strategies, a review.

PubMed

Dvorak, Ana C; Solo-Gabriele, Helena M; Galletti, Andrea; Benzecry, Bernardo; Malone, Hannah; Boguszewski, Vicki; Bird, Jason

2018-07-01

Sea levels are projected to rise in response to climate change, causing the intrusion of sea water into land. In flat coastal regions, this would generate an increase in shallow water covered areas with limited circulation. This scenario raises a concern about the consequences it could have on human health, specifically the possible impacts on disease transmission. In this review paper we identified three categories of diseases which are associated with water and whose transmission can be affected by sea level rise. These categories include: mosquitoborne diseases, naturalized organisms (Vibrio spp. and toxic algae), and fecal-oral diseases. For each disease category, we propose comprehensive adaptation strategies that would help minimize possible health risks. Finally, the City of Key West, Florida is analyzed as a case study, due to its inherent vulnerability to sea level rise. Current and projected adaptation techniques are discussed as well as the integration of additional recommendations, focused on disease transmission control. Given that sea level rise will likely continue into the future, the promotion and implementation of positive adaptation strategies is necessary to ensure community resilience. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluation of delivered dose for a clinical daily adaptive plan selection strategy for bladder cancer radiotherapy.

PubMed

Lutkenhaus, Lotte J; Visser, Jorrit; de Jong, Rianne; Hulshof, Maarten C C M; Bel, Arjan

2015-07-01

To account for variable bladder size during bladder cancer radiotherapy, a daily plan selection strategy was implemented. The aim of this study was to calculate the actually delivered dose using an adaptive strategy, compared to a non-adaptive approach. Ten patients were treated to the bladder and lymph nodes with an adaptive full bladder strategy. Interpolated delineations of bladder and tumor on a full and empty bladder CT scan resulted in five PTVs for which VMAT plans were created. Daily cone beam CT (CBCT) scans were used for plan selection. Bowel, rectum and target volumes were delineated on these CBCTs, and delivered dose for these was calculated using both the adaptive plan, and a non-adaptive plan. Target coverage for lymph nodes improved using an adaptive strategy. The full bladder strategy spared the healthy part of the bladder from a high dose. Average bowel cavity V30Gy and V40Gy significantly reduced with 60 and 69ml, respectively (p<0.01). Other parameters for bowel and rectum remained unchanged. Daily plan selection compared to a non-adaptive strategy yielded similar bladder coverage and improved coverage for lymph nodes, with a significant reduction in bowel cavity V30Gy and V40Gy only, while other sparing was limited. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Acculturation Strategies, Social Support, and Cross-Cultural Adaptation: A Mediation Analysis

ERIC Educational Resources Information Center

Ng, Ting Kin; Tsang, Kwok Kuen; Lian, Yi

2013-01-01

Previous acculturation research has established the influences of acculturation strategies and social support on cross-cultural adaptation. The present study attempted to elaborate these direct associations by proposing that social support and the use of the integration and marginalization strategies might affect psychological adaptation…

Design of Low Complexity Model Reference Adaptive Controllers

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan

2012-01-01

Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

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.

Monitoring the Performance of a Neuro-Adaptive Controller

NASA Technical Reports Server (NTRS)

Schumann, Johann; Gupta, Pramod

2004-01-01

Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

The quadruped robot adaptive control in trotting gait walking on slopes

NASA Astrophysics Data System (ADS)

Zhang, Shulong; Ma, Hongxu; Yang, Yu; Wang, Jian

2017-10-01

The quadruped robot can be decomposed into a planar seven-link closed kinematic chain in the direction of supporting line and a linear inverted pendulum in normal direction of supporting line. The ground slope can be estimated by using the body attitude information and supporting legs length. The slope degree is used in feedback, to achieve the point of quadruped robot adaptive control walking on slopes. The simulation results verify that the quadruped robot can achieves steady locomotion on the slope with the control strategy proposed in this passage.

Ten Adaptive Strategies for Family and Work Balance: Advice from Successful Families.

ERIC Educational Resources Information Center

Haddock, Shelley A.; Zimmerman, Toni Schindler; Ziemba, Scott J.; Current, Lisa R.

2001-01-01

Investigated adaptive strategies of middle class, dual earner couples (N=47) with children that are successfully managing family and work. Guided by grounded-theory methodology, analysis of interview data revealed these successful couples structured their lives around 10 major strategies. Each strategy is defined and illustrated through the…

Adaptive nonlinear control for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Black, William S.

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

A Review of Control Strategy of the Large-scale of Electric Vehicles Charging and Discharging Behavior

NASA Astrophysics Data System (ADS)

Kong, Lingyu; Han, Jiming; Xiong, Wenting; Wang, Hao; Shen, Yaqi; Li, Ying

2017-05-01

Large scale access of electric vehicles will bring huge challenges to the safe operation of the power grid, and it’s important to control the charging and discharging of the electric vehicle. First of all, from the electric quality and network loss, this paper points out the influence on the grid caused by electric vehicle charging behaviour. Besides, control strategy of electric vehicle charging and discharging has carried on the induction and the summary from the direct and indirect control. Direct control strategy means control the electric charging behaviour by controlling its electric vehicle charging and discharging power while the indirect control strategy by means of controlling the price of charging and discharging. Finally, for the convenience of the reader, this paper also proposed a complete idea of the research methods about how to study the control strategy, taking the adaptability and possibility of failure of electric vehicle control strategy into consideration. Finally, suggestions on the key areas for future research are put up.

Survey of adaptive control using Liapunov design

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Strategies for controlling item exposure in computerized adaptive testing with the partial credit model.

PubMed

Davis, Laurie Laughlin; Dodd, Barbara G

2008-01-01

Exposure control research with polytomous item pools has determined that randomization procedures can be very effective for controlling test security in computerized adaptive testing (CAT). The current study investigated the performance of four procedures for controlling item exposure in a CAT under the partial credit model. In addition to a no exposure control baseline condition, the Kingsbury-Zara, modified-within-.10-logits, Sympson-Hetter, and conditional Sympson-Hetter procedures were implemented to control exposure rates. The Kingsbury-Zara and the modified-within-.10-logits procedures were implemented with 3 and 6 item candidate conditions. The results show that the Kingsbury-Zara and modified-within-.10-logits procedures with 6 item candidates performed as well as the conditional Sympson-Hetter in terms of exposure rates, overlap rates, and pool utilization. These two procedures are strongly recommended for use with partial credit CATs due to their simplicity and strength of their results.

Model-free adaptive speed control on travelling wave ultrasonic motor

NASA Astrophysics Data System (ADS)

Di, Sisi; Li, Huafeng

2018-01-01

This paper introduced a new data-driven control (DDC) method for the speed control of ultrasonic motor (USM). The model-free adaptive control (MFAC) strategy was presented in terms of its principles, algorithms, and parameter selection. To verify the efficiency of the proposed method, a speed-frequency-time model, which contained all the measurable nonlinearity and uncertainties based on experimental data was established for simulation to mimic the USM operation system. Furthermore, the model was identified using particle swarm optimization (PSO) method. Then, the control of the simulated system using MFAC was evaluated under different expectations in terms of overshoot, rise time and steady-state error. Finally, the MFAC results were compared with that of proportion iteration differentiation (PID) to demonstrate its advantages in controlling general random system.

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.

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.

Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

DOE PAGES

Kurczy, Michael E.; Forsberg, Erica M.; Thorgersen, Michael P.; ...

2016-04-05

Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using 15NO 3 as a nitrogen source. In contrast to a control ( Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee ( Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2more » strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. In conclusion, the use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.« less

Global isotope metabolomics reveals adaptive strategies for nitrogen assimilation

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

Kurczy, Michael E.; Forsberg, Erica M.; Thorgersen, Michael P.

Nitrogen cycling is a microbial metabolic process essential for global ecological/agricultural balance. To investigate the link between the well-established ammonium and the alternative nitrate assimilation metabolic pathways, global isotope metabolomics was employed to examine three nitrate reducing bacteria using 15NO 3 as a nitrogen source. In contrast to a control ( Pseudomonas stutzeri RCH2), the results show that two of the isolates from Oak Ridge, Tennessee ( Pseudomonas N2A2 and N2E2) utilize nitrate and ammonia for assimilation concurrently with differential labeling observed across multiple classes of metabolites including amino acids and nucleotides. The data reveal that the N2A2 and N2E2more » strains conserve nitrogen-containing metabolites, indicating that the nitrate assimilation pathway is a conservation mechanism for the assimilation of nitrogen. Co-utilization of nitrate and ammonia is likely an adaption to manage higher levels of nitrite since the denitrification pathways utilized by the N2A2 and N2E2 strains from the Oak Ridge site are predisposed to the accumulation of the toxic nitrite. In conclusion, the use of global isotope metabolomics allowed for this adaptive strategy to be investigated, which would otherwise not have been possible to decipher.« less

WE-H-207B-04: Strategies for Adaptive RT

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

Green, O.

2016-06-15

In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in-room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in-room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR-driven strategies for adaptive RT workflows. The content of the sessionmore » was chosen to address both educational and practical key aspects of MR guidance. Learning Objectives: Good understanding of MR testing recommended for in-room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific); Familiarity with MR-based planning procedures: motivation, core workflow requirements, current status, challenges; Overview of the current methods for the quantification of organ motion; Discussion on approaches for adaptive treatment planning and delivery. T. Stanescu - License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system-related distortions.; T. Stanescu, N/A.« less

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

PubMed

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

2013-12-01

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

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

PubMed Central

Boeckmann, Melanie; Zeeb, Hajo

2014-01-01

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

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

PubMed

Boeckmann, Melanie; Zeeb, Hajo

2014-11-28

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

An experimental comparison of two adaptation strategies in an adaptive-walls wind-tunnel

NASA Astrophysics Data System (ADS)

Russo, G. P.; Zuppardi, G.; Basciani, M.

1995-08-01

In the present work an experimental comparison is made between two adaptation strategies: the Judd's method and the Everhart's method. A NACA 0012 airfoil has been tested at Mach numbers up to 0.4: models with chords up to 200 mm have been tested in a 200 mm × 200 mm test section. The two strategies, though based on different theoretical approaches, show a fairly good agreement as far as c p distribution on the model, lift and drag curves and residual interference are concerned and agree, in terms of lift curve slope and drag coefficient at zero lift, with the McCroskey correlation.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

Effects of incomplete adaption and disturbance in adaptive control

NASA Technical Reports Server (NTRS)

Lindorff, D. P.

1972-01-01

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

Stability and Performance Metrics for Adaptive Flight Control

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

2009-01-01

This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

Adaptive tracking control for active suspension systems with non-ideal actuators

NASA Astrophysics Data System (ADS)

Pan, Huihui; Sun, Weichao; Jing, Xingjian; Gao, Huijun; Yao, Jianyong

2017-07-01

As a critical component of transportation vehicles, active suspension systems are instrumental in the improvement of ride comfort and maneuverability. However, practical active suspensions commonly suffer from parameter uncertainties (e.g., the variations of payload mass and suspension component parameters), external disturbances and especially the unknown non-ideal actuators (i.e., dead-zone and hysteresis nonlinearities), which always significantly deteriorate the control performance in practice. To overcome these issues, this paper synthesizes an adaptive tracking control strategy for vehicle suspension systems to achieve suspension performance improvements. The proposed control algorithm is formulated by developing a unified framework of non-ideal actuators rather than a separate way, which is a simple yet effective approach to remove the unexpected nonlinear effects. From the perspective of practical implementation, the advantages of the presented controller for active suspensions include that the assumptions on the measurable actuator outputs, the prior knowledge of nonlinear actuator parameters and the uncertain parameters within a known compact set are not required. Furthermore, the stability of the closed-loop suspension system is theoretically guaranteed by rigorous mathematical analysis. Finally, the effectiveness of the presented adaptive control scheme is confirmed using comparative numerical simulation validations.

Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

PubMed

Xia, Kewei; Huo, Wei

2016-05-01

This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Static shape control for adaptive wings

NASA Astrophysics Data System (ADS)

Austin, Fred; Rossi, Michael J.; van Nostrand, William; Knowles, Gareth; Jameson, Antony

1994-09-01

A theoretical method was developed and experimentally validated, to control the static shape of flexible structures by employing internal translational actuators. A finite element model of the structure, without the actuators present, is employed to obtain the multiple-input, multiple-output control-system gain matrices for actuator-load control as well as actuator-displacement control. The method is applied to the quasistatic problem of maintaining an optimum-wing cross section during various transonic-cruise flight conditions to obtain significant reductions in the shock-induced drag. Only small, potentially achievable, adaptive modifications to the profile are required. The adaptive-wing concept employs actuators as truss elements of active ribs to reshape the wing cross section by deforming the structure. Finite element analyses of an adaptive-rib model verify the controlled-structure theory. Experiments on the model were conducted, and arbitrarily selected deformed shapes were accurately achieved.

Design of Robust Adaptive Unbalance Response Controllers for Rotors with Magnetic Bearings

NASA Technical Reports Server (NTRS)

Knospe, Carl R.; Tamer, Samir M.; Fedigan, Stephen J.

1996-01-01

Experimental results have recently demonstrated that an adaptive open loop control strategy can be highly effective in the suppression of unbalance induced vibration on rotors supported in active magnetic bearings. This algorithm, however, relies upon a predetermined gain matrix. Typically, this matrix is determined by an optimal control formulation resulting in the choice of the pseudo-inverse of the nominal influence coefficient matrix as the gain matrix. This solution may result in problems with stability and performance robustness since the estimated influence coefficient matrix is not equal to the actual influence coefficient matrix. Recently, analysis tools have been developed to examine the robustness of this control algorithm with respect to structured uncertainty. Herein, these tools are extended to produce a design procedure for determining the adaptive law's gain matrix. The resulting control algorithm has a guaranteed convergence rate and steady state performance in spite of the uncertainty in the rotor system. Several examples are presented which demonstrate the effectiveness of this approach and its advantages over the standard optimal control formulation.

Developing a consumer evaluation tool of weight control strategy advertisements on the Internet.

PubMed

Luevorasirikul, Kanokrat; Gray, Nicola J; Anderson, Claire W

2008-06-01

To develop two evaluation tools for weight loss and weight gain advertisements on the Internet in order to help consumers to evaluate the quality of information within these advertisements. One hundred websites identified by Internet search engines for weight loss and weight gain strategies (50 websites each) were evaluated using two specific scoring instruments, developed by adapting questions from the 'DISCERN' tool and reviewing all related weight control guidelines and advertising regulations. The validity and reliability of the adapted tools were tested. Our evaluation tools rated the information from most websites as poor quality (70%). In the case of weight loss strategies, statements about rapid (18%) and permanent (28%) weight loss caused concern as well as lack of sensible advice about dieting and a lack of product warnings (84%). Safety concerns relating to weight gain products were the lack of warnings about side effects in products containing steroids and creatine (92%). The adapted tools exhibited acceptable validity and reliability. Quality of information within weight control advertisements on the Internet was generally poor. Problems of false claims, little advice on healthy ways to modify weight and few warnings on side effects have been highlighted in this study.

A new approach to adaptive control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

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

Adaptive relative pose control for autonomous spacecraft rendezvous and proximity operations with thrust misalignment and model uncertainties

NASA Astrophysics Data System (ADS)

Sun, Liang; Zheng, Zewei

2017-04-01

An adaptive relative pose control strategy is proposed for a pursue spacecraft in proximity operations on a tumbling target. Relative position vector between two spacecraft is required to direct towards the docking port of the target while the attitude of them must be synchronized. With considering the thrust misalignment of pursuer, an integrated controller for relative translational and relative rotational dynamics is developed by using norm-wise adaptive estimations. Parametric uncertainties, unknown coupled dynamics, and bounded external disturbances are compensated online by adaptive update laws. It is proved via Lyapunov stability theory that the tracking errors of relative pose converge to zero asymptotically. Numerical simulations including six degrees-of-freedom rigid body dynamics are performed to demonstrate the effectiveness of the proposed controller.

Computational model for behavior shaping as an adaptive health intervention strategy.

PubMed

Berardi, Vincent; Carretero-González, Ricardo; Klepeis, Neil E; Ghanipoor Machiani, Sahar; Jahangiri, Arash; Bellettiere, John; Hovell, Melbourne

2018-03-01

Adaptive behavioral interventions that automatically adjust in real-time to participants' changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated.

A Novel Approach to Adaptive Flow Separation Control

DTIC Science & Technology

2016-09-03

particular, it considers control of flow separation over a NACA-0025 airfoil using microjet actuators and develops Adaptive Sampling Based Model...Predictive Control ( Adaptive SBMPC), a novel approach to Nonlinear Model Predictive Control that applies the Minimal Resource Allocation Network...Distribution Unlimited UU UU UU UU 03-09-2016 1-May-2013 30-Apr-2016 Final Report: A Novel Approach to Adaptive Flow Separation Control The views, opinions

Dual adaptive control: Design principles and applications

NASA Technical Reports Server (NTRS)

Mookerjee, Purusottam

1988-01-01

The design of an actively adaptive dual controller based on an approximation of the stochastic dynamic programming equation for a multi-step horizon is presented. A dual controller that can enhance identification of the system while controlling it at the same time is derived for multi-dimensional problems. This dual controller uses sensitivity functions of the expected future cost with respect to the parameter uncertainties. A passively adaptive cautious controller and the actively adaptive dual controller are examined. In many instances, the cautious controller is seen to turn off while the latter avoids the turn-off of the control and the slow convergence of the parameter estimates, characteristic of the cautious controller. The algorithms have been applied to a multi-variable static model which represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. Monte Carlo comparisons based on parametric and nonparametric statistical analysis indicate the superiority of the dual controller over the baseline controller.

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.

Adapting Strategies of Effective Instruction for Culturally Diverse Preschoolers

ERIC Educational Resources Information Center

Yamauchi, Lois A.; Im, Seongah; Schonleber, Nanette S.

2012-01-01

This article describes collaboration between preschool and university educators focused on adapting the Center for Research on Education, Diversity, and Excellence (CREDE) standards for Effective Pedagogy for use in early childhood (EC) settings. The CREDE standards are strategies of best practices for culturally diverse K-12 students. Teachers…

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions.

PubMed

Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E; Downs, Danielle S; Savage, Jennifer S

2014-06-01

Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or "just-in-time" behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components.

Determinants of climate change adaptation strategies used by fish farmers in Epe Local Government Area of Lagos State, Nigeria.

PubMed

Arimi, Kayode S

2014-05-01

Undesirable impacts of climate change have been a common occurrence that has made fish farmers in developing countries adopt some climate-change adaptation strategies. However, little is known about determinants of climate-change adaptation strategies used by these fish farmers. This study, therefore, articulates novelties on adaptation to climate change, as well ascertains determinants of adaptation strategies used by fish farmers in Epe, Lagos State, Nigeria. Climate change adaptation strategies mostly used by fish farmers include frequent seeking for early warning information about climate change (76.7%) and avoidance of areas susceptible to flooding (60.0%). Climate-change adaptation strategies used by fish farmers were significantly influenced by access to early warning information (β = 7.21), knowledge of farmers about climate change adaptation strategies (β = 8.86), access to capital (β = 28.25), and participation in workshop and conferences (β = 37.19) but were reduced by number of fish stocking (β = -2.06). The adaptation strategies used by fish farmers were autonomous and mostly determined by the access to credit facilities and information. Development policy should focus on carbon capture and storage technology in order to reduce adverse impacts of climate change, as well as making early warning information on climate change available to fish farmers. These will enhance adaptation to climate change. © 2013 Society of Chemical Industry.

Adaptive Inverse Control for Rotorcraft Vibration Reduction

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.

1985-01-01

This thesis extends the Least Mean Square (LMS) algorithm to solve the mult!ple-input, multiple-output problem of alleviating N/Rev (revolutions per minute by number of blades) helicopter fuselage vibration by means of adaptive inverse control. A frequency domain locally linear model is used to represent the transfer matrix relating the higher harmonic pitch control inputs to the harmonic vibration outputs to be controlled. By using the inverse matrix as the controller gain matrix, an adaptive inverse regulator is formed to alleviate the N/Rev vibration. The stability and rate of convergence properties of the extended LMS algorithm are discussed. It is shown that the stability ranges for the elements of the stability gain matrix are directly related to the eigenvalues of the vibration signal information matrix for the learning phase, but not for the control phase. The overall conclusion is that the LMS adaptive inverse control method can form a robust vibration control system, but will require some tuning of the input sensor gains, the stability gain matrix, and the amount of control relaxation to be used. The learning curve of the controller during the learning phase is shown to be quantitatively close to that predicted by averaging the learning curves of the normal modes. For higher order transfer matrices, a rough estimate of the inverse is needed to start the algorithm efficiently. The simulation results indicate that the factor which most influences LMS adaptive inverse control is the product of the control relaxation and the the stability gain matrix. A small stability gain matrix makes the controller less sensitive to relaxation selection, and permits faster and more stable vibration reduction, than by choosing the stability gain matrix large and the control relaxation term small. It is shown that the best selections of the stability gain matrix elements and the amount of control relaxation is basically a compromise between slow, stable convergence and fast

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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.

Application of fuzzy adaptive control to a MIMO nonlinear time-delay pump-valve system.

PubMed

Lai, Zhounian; Wu, Peng; Wu, Dazhuan

2015-07-01

In this paper, a control strategy to balance the reliability against efficiency is introduced to overcome the common off-design operation problem in pump-valve systems. The pump-valve system is a nonlinear multi-input-multi-output (MIMO) system with time delays which cannot be accurately measured but can be approximately modeled using Bernoulli Principle. A fuzzy adaptive controller is applied to approximate system parameters and achieve the control of delay-free model since the system model is inaccurate and the direct feedback linearization method cannot be applied. An extended Smith predictor is introduced to compensate time delays of the system using the inaccurate system model. The experiment is carried out to verify the effectiveness of the control strategy whose results show that the control performance is well achieved. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Climate change impacts and adaptive strategies: lessons from the grapevine.

PubMed

Mosedale, Jonathan R; Abernethy, Kirsten E; Smart, Richard E; Wilson, Robert J; Maclean, Ilya M D

2016-11-01

The cultivation of grapevines for winemaking, known as viticulture, is widely cited as a climate-sensitive agricultural system that has been used as an indicator of both historic and contemporary climate change. Numerous studies have questioned the viability of major viticulture regions under future climate projections. We review the methods used to study the impacts of climate change on viticulture in the light of what is known about the effects of climate and weather on the yields and quality of vineyard harvests. Many potential impacts of climate change on viticulture, particularly those associated with a change in climate variability or seasonal weather patterns, are rarely captured. Key biophysical characteristics of viticulture are often unaccounted for, including the variability of grapevine phenology and the exploitation of microclimatic niches that permit successful cultivation under suboptimal macroclimatic conditions. We consider how these same biophysical characteristics permit a variety of strategies by which viticulture can adapt to changing climatic conditions. The ability to realize these strategies, however, is affected by uneven exposure to risks across the winemaking sector, and the evolving capacity for decision-making within and across organizational boundaries. The role grape provenance plays in shaping perceptions of wine value and quality illustrates how conflicts of interest influence decisions about adaptive strategies within the industry. We conclude by considering what lessons can be taken from viticulture for studies of climate change impacts and the capacity for adaptation in other agricultural and natural systems. © 2016 John Wiley & Sons Ltd.

A survey of adaptive control technology in robotics

NASA Technical Reports Server (NTRS)

Tosunoglu, S.; Tesar, D.

1987-01-01

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

Closing the Certification Gaps in Adaptive Flight Control Software

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.

2008-01-01

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Enhanced vaccine control of epidemics in adaptive networks

NASA Astrophysics Data System (ADS)

Shaw, Leah B.; Schwartz, Ira B.

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

Enhanced vaccine control of epidemics in adaptive networks.

PubMed

Shaw, Leah B; Schwartz, Ira B

2010-04-01

We study vaccine control for disease spread on an adaptive network modeling disease avoidance behavior. Control is implemented by adding Poisson-distributed vaccination of susceptibles. We show that vaccine control is much more effective in adaptive networks than in static networks due to feedback interaction between the adaptive network rewiring and the vaccine application. When compared to extinction rates in static social networks, we find that the amount of vaccine resources required to sustain similar rates of extinction are as much as two orders of magnitude lower in adaptive networks.

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.

Adaptive and Qualitative Changes in Encoding Strategy With Experience: Evidence From the Test-Expectancy Paradigm

PubMed Central

Finley, Jason R.; Benjamin, Aaron S.

2012-01-01

Three experiments demonstrated learners’ abilities to adaptively and qualitatively accommodate their encoding strategies to the demands of an upcoming test. Stimuli were word pairs. In Experiment 1, test expectancy was induced for either cued recall (of targets given cues) or free recall (of targets only) across 4 study–test cycles of the same test format, followed by a final critical cycle featuring either the expected or the unexpected test format. For final tests of both cued and free recall, participants who had expected that test format outperformed those who had not. This disordinal interaction, supported by recognition and self-report data, demonstrated not mere differences in effort based on anticipated test difficulty, but rather qualitative and appropriate differences in encoding strategies based on expected task demands. Participants also came to appropriately modulate metacognitive monitoring (Experiment 2) and study-time allocation (Experiment 3) across study–test cycles. Item and associative recognition performance, as well as self-report data, revealed shifts in encoding strategies across trials; these results were used to characterize and evaluate the different strategies that participants employed for cued versus free recall and to assess the optimality of participants’ metacognitive control of encoding strategies. Taken together, these data illustrate a sophisticated form of metacognitive control, in which learners qualitatively shift encoding strategies to match the demands of anticipated tests. PMID:22103783

An innovative cross-sectoral method for implementation of trade-off adaptation strategy assessment under climate change

NASA Astrophysics Data System (ADS)

Tsao, Jung-Hsuan; Tung, Ching-Pin; Liu, Tzu-Ming

2014-05-01

Climate change will increase sharp risks to the water and food supply in coming decades. Although impact assessment and adaptation evaluation has been discussed a lot in recent years, the importance of adaptation implement should not be ignored. In Taiwan, and elsewhere, fallow is an option of adaptation strategy under climate change. Fallow would improve the water scarcity of domestic use, but the food security might be threatened. The trade-off effects of adaptation actions are just like the side effects of medicine which cannot be avoided. Thus, managing water resources with an integrated approach will be urgent. This study aims to establish a cross-sectoral framework for implementation the trade-off adaptation strategy. Not only fallow, but also other trade-off strategy like increasing the percentage of national grain self-sufficiency would be analyzed by a rational decision process. The recent percentage of grain self-sufficiency in Taiwan is around 32, which was decreasing from 53 thirty years ago. Yet, the goal of increasing grain self-sufficiency means much more water must be used in agriculture. In that way, domestic users may face the water shortage situation. Considering the conflicts between water supply and food security, the concepts from integrative negotiation are appropriate to apply. The implementation of trade-off adaptation strategies needs to start by quantifying the utility of water supply and food security were be quantified. Next, each side's bottom line can be found by BATNA (Best Alternative to a Negotiated Agreement) and ZOPA (Zone of Possible Agreement). ZOPA provides the entire possible outcomes, and BATNA ensures the efficiency of adaptation actions by moving along with Pareto frontier. Therefore, the optimal percentage of fallow and grain self-sufficiency can be determined. Furthermore, BATNA also provides the pathway step by step which can be a guideline of adaptation strategies. This framework allows analysts and stakeholder to

RHODES-ITMS Tempe field test project : implementation and field testing of RHODES, a real-time traffic adaptive control system

DOT National Transportation Integrated Search

2001-09-01

RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchang...

Parameter Estimation for a Hybrid Adaptive Flight Controller

NASA Technical Reports Server (NTRS)

Campbell, Stefan F.; Nguyen, Nhan T.; Kaneshige, John; Krishnakumar, Kalmanje

2009-01-01

This paper expands on the hybrid control architecture developed at the NASA Ames Research Center by addressing issues related to indirect adaptation using the recursive least squares (RLS) algorithm. Specifically, the hybrid control architecture is an adaptive flight controller that features both direct and indirect adaptation techniques. This paper will focus almost exclusively on the modifications necessary to achieve quality indirect adaptive control. Additionally this paper will present results that, using a full non -linear aircraft model, demonstrate the effectiveness of the hybrid control architecture given drastic changes in an aircraft s dynamics. Throughout the development of this topic, a thorough discussion of the RLS algorithm as a system identification technique will be provided along with results from seven well-known modifications to the popular RLS algorithm.

Ten adaptive strategies for family and work balance: advice from successful families.

PubMed

Haddock, S A; Zimmerman, T S; Ziemba, S J; Current, L R

2001-10-01

Despite negative media images and social dynamics insensitive to the lives of many dual-career couples, research shows that these families are largely healthy and thriving. In this study, we investigated the adaptive strategies of middle-class, dual-earner couples (N = 47) with children that are successfully managing family and work. Guided by grounded-theory methodology, analysis of interview data revealed that these successful couples structured their lives around 10 major strategies: Valuing family, striving for partnership, deriving meaning from work, maintaining work boundaries, focusing and producing at work, taking pride in dual earning, prioritizing family fun, living simply, making decisions proactively, and valuing time. Each adaptive strategy is defined and illustrated through the participants' own words. Clinical applications for therapists working with dual-earner couples are offered.

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

Systems and Methods for Derivative-Free Adaptive Control

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

Adaptive wing static aeroelastic roll control

NASA Astrophysics Data System (ADS)

Ehlers, Steven M.; Weisshaar, Terrence A.

1993-09-01

Control of the static aeroelastic characteristics of a swept uniform wing in roll using an adaptive structure is examined. The wing structure is modeled as a uniform beam with bending and torsional deformation freedom. Aerodynamic loads are obtained from strip theory. The structure model includes coefficients representing torsional and bending actuation provided by embedded piezoelectric material layers. The wing is made adaptive by requiring the electric field applied to the piezoelectric material layers to be proportional to the wing root loads. The proportionality factor, or feedback gain, is used to control static aeroelastic rolling properties. Example wing configurations are used to illustrate the capabilities of the adaptive structure. The results show that rolling power, damping-in-roll and aileron effectiveness can be controlled by adjusting the feedback gain. And that dynamic pressure affects the gain required. Gain scheduling can be used to set and maintain rolling properties over a range of dynamic pressures. An adaptive wing provides a method for active aeroelastic tailoring of structural response to meet changing structural performance requirements during a roll maneuver.

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.

Design of smart composite platforms for adaptive trust vector control and adaptive laser telescope for satellite applications

NASA Astrophysics Data System (ADS)

Ghasemi-Nejhad, Mehrdad N.

2013-04-01

designed to have tip-tilt pointing and simultaneous multi-degree-of-freedom vibration isolation capability for pointing stabilization. Analytical approaches have been employed for determining the loads in the components as well as optimizing the design of the system. The different critical components such as telescope tube struts, flexure joints, and the secondary mirror mount have been designed and analyzed using finite element technique. The Simultaneous Precision Positioning and Vibration Suppression (SPPVS) smart composites platforms for the adaptive TVC and adaptive composite telescope are analogous (e.g., see work by Ghasemi-Nejhad and co-workers [1, 2]), where innovative concepts and control strategies are introduced, and experimental verifications of simultaneous thrust vector control and vibration isolation of satellites were performed. The smart composite platforms function as an active structural interface between the main thruster of a satellite and the satellite structure for the adaptive TVC application and as an active structural interface between the main smart composite telescope and the satellite structure for the adaptive laser communication application. The cascaded multiple feedback loops compensate the hysteresis (for piezoelectric stacks inside the three linear actuators that individually have simultaneous precision positioning and vibration suppression), dead-zone, back-lash, and friction nonlinearities very well, and provide precision and quick smart platform control and satisfactory thrust vector control capability. In addition, for example for the adaptive TVC, the experimental results show that the smart composite platform satisfactorily provided precision and fast smart platform control as well as the satisfactory thrust vector control capability. The vibration controller isolated 97% of the vibration energy due to the thruster firing.

Experimental aeroelastic control using adaptive wing model concepts

NASA Astrophysics Data System (ADS)

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

2001-06-01

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

Adaptive Control for Microgravity Vibration Isolation System

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

FAB (Functionally Alert Behavior Strategies) to Improve Self-Control

ERIC Educational Resources Information Center

Pagano, John

2015-01-01

This paper describes the FAB (Functionally Alert Behavior) Strategies approach to improve behavior in children and adolescents with complex behavioral challenges. FAB Strategies include evidence-based environmental adaptations, sensory modulation, positive behavioral support, and physical self-regulation strategies. FAB Strategies can be used by…

A review of climate-change adaptation strategies for wildlife management and biodiversity conservation.

PubMed

Mawdsley, Jonathan R; O'Malley, Robin; Ojima, Dennis S

2009-10-01

The scientific literature contains numerous descriptions of observed and potential effects of global climate change on species and ecosystems. In response to anticipated effects of climate change, conservation organizations and government agencies are developing "adaptation strategies" to facilitate the adjustment of human society and ecological systems to altered climate regimes. We reviewed the literature and climate-change adaptation plans that have been developed in United States, Canada, England, México, and South Africa and found 16 general adaptation strategies that relate directly to the conservation of biological diversity. These strategies can be grouped into four broad categories: land and water protection and management; direct species management; monitoring and planning; and law and policy. Tools for implementing these strategies are similar or identical to those already in use by conservationists worldwide (land and water conservation, ecological restoration, agrienvironment schemes, species translocation, captive propagation, monitoring, natural resource planning, and legislation/regulation). Although our review indicates natural resource managers already have many tools that can be used to address climate-change effects, managers will likely need to apply these tools in novel and innovative ways to meet the unprecedented challenges posed by climate change.

Adaptive governance and institutional strategies for climate-induced community relocations in Alaska.

PubMed

Bronen, Robin; Chapin, F Stuart

2013-06-04

This article presents governance and institutional strategies for climate-induced community relocations. In Alaska, repeated extreme weather events coupled with climate change-induced coastal erosion impact the habitability of entire communities. Community residents and government agencies concur that relocation is the only adaptation strategy that can protect lives and infrastructure. Community relocation stretches the financial and institutional capacity of existing governance institutions. Based on a comparative analysis of three Alaskan communities, Kivalina, Newtok, and Shishmaref, which have chosen to relocate, we examine the institutional constraints to relocation in the United States. We identify policy changes and components of a toolkit that can facilitate community-based adaptation when environmental events threaten people's lives and protection in place is not possible. Policy changes include amendment of the Stafford Act to include gradual geophysical processes, such as erosion, in the statutory definition of disaster and the creation of an adaptive governance framework to allow communities a continuum of responses from protection in place to community relocation. Key components of the toolkit are local leadership and integration of social and ecological well-being into adaptation planning.

Robust adaptive antiswing control of underactuated crane systems with two parallel payloads and rail length constraint.

PubMed

Zhang, Zhongcai; Wu, Yuqiang; Huang, Jinming

2016-11-01

The antiswing control and accurate positioning are simultaneously investigated for underactuated crane systems in the presence of two parallel payloads on the trolley and rail length limitation. The equations of motion for the crane system in question are established via the Euler-Lagrange equation. An adaptive control strategy is proposed with the help of system energy function and energy shaping technique. Stability analysis shows that under the designed adaptive controller, the payload swings can be suppressed ultimately and the trolley can be regulated to the destination while not exceeding the pre-specified boundaries. Simulation results are provided to show the satisfactory control performances of the presented control method in terms of working efficiency as well as robustness with respect to external disturbances. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

An adaptive radiotherapy planning strategy for bladder cancer using deformation vector fields.

PubMed

Vestergaard, Anne; Kallehauge, Jesper Folsted; Petersen, Jørgen Breede Baltzer; Høyer, Morten; Søndergaard, Jimmi; Muren, Ludvig Paul

2014-09-01

Adaptive radiotherapy (ART) has considerable potential in treatment of bladder cancer due to large inter-fractional changes in shape and size of the target. The aim of this study was to compare our clinically applied method for plan library creation that involves manual bladder delineations (Clin-ART) with a method using the deformation vector fields (DVFs) resulting from intensity-based deformable image registrations (DVF-based ART). The study included thirteen patients with urinary bladder cancer who had daily cone beam CTs (CBCTs) acquired for set-up. In both ART strategies investigated, three plan selection volumes were generated using the CBCTs from the first four fractions; in Clin-ART boolean combinations of delineated bladders were used, while the DVF-based strategy applied combinations of the mean and standard deviation of patient-specific DVFs. The volume ratios (VRs) of the course-averaged PTV for the two ART strategies relative the non-adaptive PTV were calculated. Both Clin-ART and DVF-based ART considerably reduced the course-averaged PTV, compared to non-adaptive RT. The VR for DVF-based ART was lower than for Clin-ART (0.65 vs. 0.73; p<0.01). DVF-based ART for bladder irradiation has a considerable normal tissue sparing potential surpassing our already highly conformal clinically applied ART strategy. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Robust Adaptive Control Using a Filtering Action

DTIC Science & Technology

2009-09-01

research performed on this class of control systems , sensitivity to external disturbances and modeling errors together with poor transient response...dissertation, we address the problems of designing a class of Adaptive Control systems which yield fast adaptation, thus good transient response, and...unable to stabilize the system . Although this approach requires more knowledge about the system in order to control it, it is still attractive in cases

Relationships Among Adaptive and Maladaptive Emotion Regulation Strategies and Psychopathology During the Treatment of Comorbid Anxiety and Alcohol Use Disorders

PubMed Central

Conklin, Laren R.; Cassiello-Robbins, Clair; Brake, C. Alex; Sauer-Zavala, Shannon; Farchione, Todd J.; Ciraulo, Domenic A.; Barlow, David H.

2015-01-01

Both maladaptive and adaptive emotion regulation strategies have been linked with psychopathology. However, previous studies have largely examined them separately, and little research has examined the interplay of these strategies cross-sectionally or longitudinally in patients undergoing psychological treatment. This study examined the use and interplay of adaptive and maladaptive emotion regulation strategies in 81 patients receiving cognitive-behavioral interventions for comorbid alcohol use and anxiety disorders. Patients completed measures of emotion regulation strategy use and symptoms of psychopathology pre- and post-treatment. Cross-sectionally, higher use of maladaptive strategies (e.g., denial) was significantly related to higher psychopathology pre- and post-treatment, whereas higher use of adaptive strategies (e.g., acceptance) only significantly related to lower psychopathology post-treatment. Prospectively, changes in maladaptive strategies, but not changes in adaptive strategies, were significantly associated with post-treatment psychopathology. However, for patients with higher pre-treatment maladaptive strategy use, gains in adaptive strategies were significantly associated with lower post-treatment psychopathology. These findings suggest that psychological treatments may maximize efficacy by considering patient skill use at treatment outset. By better understanding a patient's initial emotion regulation skills, clinicians may be better able to optimize treatment outcomes by emphasizing maladaptive strategy use reduction predominately, or in conjunction with increasing adaptive skill use. PMID:26310363

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.

An adaptive strategy for reducing Feral Cat predation on endangered hawaiian birds

USGS Publications Warehouse

Hess, S.C.; Banko, P.C.; Hansen, H.

2009-01-01

Despite the long history of Feral Cats Felis catus in Hawai'i, there has been little research to provide strategies to improve control programmes and reduce depredation on endangered species. Our objective Was to develop a predictive model to determine how landscape features on Mauna Kea, such as habitat, elevation, and proximity to roads, may affect the number of Feral Cats captured at each trap. We used log-link generalized linear models and QAIC c model ranking criteria to determine the effect of these factors. We found that The number of cats captured per trap Was related to effort, habitat type, and Whether traps Were located on The West or North Slope of Mauna Kea. We recommend an adaptive management strategy to minimize trapping interference by non-target Small Indian Mongoose Herpestes auropunctatus with toxicants, to focus trapping efforts in M??mane Sophora chrysophylla habitat on the West slope of Mauna Kea, and to cluster traps near others that have previously captured multiple cats.

Adapting global influenza management strategies to address emerging viruses.

PubMed

Noah, Diana L; Noah, James W

2013-07-15

Death by respiratory complications from influenza infections continues to be a major global health concern. Antiviral drugs are widely available for therapy and prophylaxis, but viral mutations have resulted in resistance that threatens to reduce the long-term utility of approved antivirals. Vaccination is the best method for controlling influenza, but vaccine strategies are blunted by virus antigenic drift and shift. Genetic shift in particular has led to four pandemics in the last century, which have prompted the development of efficient global surveillance and vaccination programs. Although the influenza pandemic of 2009 emphasized the need for the rapid standardization of global surveillance methods and the preparation and dissemination of global assay standards for improved reporting and diagnostic tools, outbreaks of novel influenza strains continue to occur, and current efforts must be enhanced by aggressive public education programs to promote increased vaccination rates in the global population. Recently, a novel H7N9 avian influenza virus with potential to become a pandemic strain emerged in China and was transmitted from animals to humans with a demonstrated >20% mortality rate. Sporadic outbreaks of highly lethal avian virus strains have already increased public awareness and altered annual vaccine production strategies to prevent the natural adaption of this virus to human-to-human transmission. Additional strategies for combating influenza include advancement of new antivirals for unexploited viral or host cellular targets; novel adjuvants and alternate vaccine delivery systems; and development of universal protein, DNA, or multivalent vaccines designed to increase immune responsiveness and enhance public health response times.

Evaluation of early antimicrobial therapy adaptation guided by the BetaLACTA® test: a case-control study.

PubMed

Garnier, Marc; Rozencwajg, Sacha; Pham, Tài; Vimont, Sophie; Blayau, Clarisse; Hafiani, Mehdi; Fulgencio, Jean-Pierre; Bonnet, Francis; Mainardi, Jean-Luc; Arlet, Guillaume; Fartoukh, Muriel; Gallah, Salah; Quesnel, Christophe

2017-06-28

Rapid diagnostic tests detecting microbial resistance are needed for limiting the duration of inappropriateness of empirical antimicrobial therapy (EAT) in intensive care unit patients, besides reducing the use of broad-spectrum antibiotics. We hypothesized that the betaLACTA® test (BLT) could lead to early increase in the adequacy of antimicrobial therapy. This was a case-control study. Sixty-one patients with BLT-guided adaptation of EAT were prospectively included, and then matched with 61 "controls" having similar infection characteristics (community or hospital-acquired, and source of infection), in whom EAT was conventionally adapted to antibiogram results. Endpoints were to compare the proportion of appropriate (primary endpoint) and optimal (secondary endpoint) antimicrobial therapies with each of the two strategies, once microbiological sample culture results were available. Characteristics of patients, infections and EAT at inclusion were similar between groups. Nine early escalations of EAT occurred in the BLT-guided adaptation group, reaching 98% appropriateness vs. 77% in the conventional adaptation group (p < 0.01). The BLT reduced the time until escalation of an inappropriate EAT from 50.5 (48-73) to 27 (24-28) hours (p < 0.01). Seventeen early de-escalations occurred in the BLT-guided adaptation group, compared to one in the conventional adaptation group, reducing patients' exposure to broad-spectrum beta-lactam such as carbapenems. In multivariate analysis, use of the BLT was strongly associated with early appropriate (OR = 18 (3.4-333.8), p = 0.006) and optimal (OR = 35.5 (9.6-231.9), p < 0.001) antimicrobial therapies. Safety parameters were similar between groups. Our study suggests that a BLT-guided adaptation strategy may allow early beta-lactam adaptation from the first 24 hours following the beginning of sepsis management.

Some design guidelines for discrete-time adaptive controllers

NASA Technical Reports Server (NTRS)

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

1985-01-01

There have been many algorithms proposed for adaptive control which will provide globally asymptotically stable controllers if some stringent conditions on the plant are met. The conditions on the plant cannot be met in practice as all plants will contain high frequency unmolded dynamics therefore, blind implementation of the published algorithms can lead to disastrous results. This paper uses a linearization analysis of a non-linear adaptive controller to demonstrate analytically design guidelines which aleviate some of the problems associated with adaptive control in the presence of unmodeled dynamics.

Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras

NASA Astrophysics Data System (ADS)

Guo, Dejun; Bourne, Joseph R.; Wang, Hesheng; Yim, Woosoon; Leang, Kam K.

2017-08-01

This paper presents the design and implementation of an adaptive-repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. Applications of this control strategy include the use of high-flying unmanned aerial vehicles (UAVs) with computer vision for monitoring, controlling, and coordinating the movements of lower altitude agents in areas, for example, where GPS signals may be unreliable or nonexistent. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame. Due to the circular motion of the HFV, the resulting motion trajectory of the LFV in the image frame can be periodic in time, thus an adaptive-repetitive control system is exploited for regulation and/or trajectory tracking. The adaptive control law is able to handle uncertainties in the camera's intrinsic and extrinsic parameters. The design and stability analysis of the closed-loop control system is presented, where Lyapunov stability is shown. Simulation and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter, demonstrating the capabilities of the visual-servo control system for localization (i.e.,, motion capturing) and trajectory tracking control. In fact, results show that the LFV can be commanded to hover in place as well as track a user-defined flower-shaped closed trajectory, while the HFV and camera system circulates above with constant angular velocity. On average, the proposed adaptive-repetitive visual-servo control system reduces the average RMS tracking error by over 77% in the image plane and over 71% in the world frame compared to using just the adaptive visual-servo control law.

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.

Convergence of an hp-Adaptive Finite Element Strategy in Two and Three Space-Dimensions

NASA Astrophysics Data System (ADS)

Bürg, Markus; Dörfler, Willy

2010-09-01

We show convergence of an automatic hp-adaptive refinement strategy for the finite element method on the elliptic boundary value problem. The strategy is a generalization of a refinement strategy proposed for one-dimensional situations to problems in two and three space-dimensions.

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.

On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2011-01-01

This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.

Adaptive Control Of Remote Manipulator

NASA Technical Reports Server (NTRS)

Seraji, Homayoun

1989-01-01

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

L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.

PubMed

Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei

2011-06-01

In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.

Decentralized digital adaptive control of robot motion

NASA Technical Reports Server (NTRS)

Tarokh, M.

1990-01-01

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

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

NASA Astrophysics Data System (ADS)

Estève, Simon J.; Johnson, Marty E.

2005-12-01

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

Algebraic and adaptive learning in neural control systems

NASA Astrophysics Data System (ADS)

Ferrari, Silvia

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

Adaptive Modal Identification for Flutter Suppression Control

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

NASA Astrophysics Data System (ADS)

Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

2013-01-01

Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Comparison of Different Strategies for Selection/Adaptation of Mixed Microbial Cultures Able to Ferment Crude Glycerol Derived from Second-Generation Biodiesel.

PubMed

Varrone, C; Heggeset, T M B; Le, S B; Haugen, T; Markussen, S; Skiadas, I V; Gavala, H N

2015-01-01

Objective of this study was the selection and adaptation of mixed microbial cultures (MMCs), able to ferment crude glycerol generated from animal fat-based biodiesel and produce building-blocks and green chemicals. Various adaptation strategies have been investigated for the enrichment of suitable and stable MMC, trying to overcome inhibition problems and enhance substrate degradation efficiency, as well as generation of soluble fermentation products. Repeated transfers in small batches and fed-batch conditions have been applied, comparing the use of different inoculum, growth media, and Kinetic Control. The adaptation of activated sludge inoculum was performed successfully and continued unhindered for several months. The best results showed a substrate degradation efficiency of almost 100% (about 10 g/L glycerol in 21 h) and different dominant metabolic products were obtained, depending on the selection strategy (mainly 1,3-propanediol, ethanol, or butyrate). On the other hand, anaerobic sludge exhibited inactivation after a few transfers. To circumvent this problem, fed-batch mode was used as an alternative adaptation strategy, which led to effective substrate degradation and high 1,3-propanediol and butyrate production. Changes in microbial composition were monitored by means of Next Generation Sequencing, revealing a dominance of glycerol consuming species, such as Clostridium, Klebsiella, and Escherichia.

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.

Projection Operator: A Step Towards Certification of Adaptive Controllers

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Robust adaptive control for a hybrid solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Snyder, Steven

2011-12-01

Solid oxide fuel cells (SOFCs) are electrochemical energy conversion devices. They offer a number of advantages beyond those of most other fuel cells due to their high operating temperature (800-1000°C), such as internal reforming, heat as a byproduct, and faster reaction kinetics without precious metal catalysts. Mitigating fuel starvation and improving load-following capabilities of SOFC systems are conflicting control objectives. However, this can be resolved by the hybridization of the system with an energy storage device, such as an ultra-capacitor. In this thesis, a steady-state property of the SOFC is combined with an input-shaping method in order to address the issue of fuel starvation. Simultaneously, an overall adaptive system control strategy is employed to manage the energy sharing between the elements as well as to maintain the state-of-charge of the energy storage device. The adaptive control method is robust to errors in the fuel cell's fuel supply system and guarantees that the fuel cell current and ultra-capacitor state-of-charge approach their target values and remain uniformly, ultimately bounded about these target values. Parameter saturation is employed to guarantee boundedness of the parameters. The controller is validated through hardware-in-the-loop experiments as well as computer simulations.

Least-Squares Adaptive Control Using Chebyshev Orthogonal Polynomials

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

NASA Astrophysics Data System (ADS)

Roslund, Jonathan; Shir, Ofer M.; Bäck, Thomas; Rabitz, Herschel

2009-10-01

Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to ˜9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem’s Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape’s local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.

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.

Impacts of adaptive flood management strategies on the Socio-Hydrological system in Ganges - Brahmaputra river basin, Bangladesh

NASA Astrophysics Data System (ADS)

Sung, K.; Jeong, H.; Sangwan, N.; Yu, D. J.

2017-12-01

Human societies have tried to prevent floods by building robust infrastructure such as levees or dams. However, some scholars raise a doubt to this approach because of a lack of adaptiveness to environmental and societal changes in a long-term. Thus, a growing number of studies now suggest adopting new strategies in flood management to reinforce an adapt capacity to the long-term flood risk. This study addresses this issue by developing a conceptual mathematical model exploring how flood management strategies effect to the dynamics human-flood interaction, ultimately the flood resilience in a long-term. Especially, our model is motivated by the community-based flood protection system in southwest coastal area in Bangladesh. We developed several conceptual flood management strategies and investigated the interplay between those strategies and community's capacity to cope with floods. We additionally analyzed how external disturbances (sea level rise, water tide level change, and outside economic development) alter the adaptive capacity to flood risks. The results of this study reveal that the conventional flood management has potential vulnerabilities as external disturbances increase. Our results also highlight the needs of the adaptive strategy as a new paradigm in flood management which is able to feedback to the social and hydrological conditions. These findings provide insights on the resilience-based, adaptive strategies which can build flood resilience under global change.

A novel fuzzy-logic control strategy minimizing N2O emissions.

PubMed

Boiocchi, Riccardo; Gernaey, Krist V; Sin, Gürkan

2017-10-15

A novel control strategy for achieving low N 2 O emissions and low effluent NH 4 + concentration is here proposed. The control strategy uses the measurements of ammonium and nitrate concentrations in inlet and outlet of the aerobic zone of a wastewater treatment plant to calculate a ratio indicating the balance among the microbial groups. More specifically, the ratio will indicate if there is a complete nitrification. In case nitrification is not complete, the controller will adjust the aeration level of the plant in order to inhibit the production of N 2 O from AOB and HB denitrification. The controller was implemented using the fuzzy logic approach. It was comprehensively tested for different model structures and different sets of model parameters with regards to its ability of mitigating N 2 O emissions for future applications in real wastewater treatment plants. It is concluded that the control strategy is useful for those plants having AOB denitrification as the main N 2 O producing process. However, in treatment plants having incomplete NH 2 OH oxidation as the main N 2 O producing pathway, a cascade controller configuration adapting the oxygen supply to respect only the effluent ammonium concentration limits was found to be more effective to ensure low N 2 O emissions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Socio-economic vulnerability of coastal communities in southern Thailand: the development of adaptation strategies

NASA Astrophysics Data System (ADS)

Willroth, P.; Massmann, F.; Wehrhahn, R.; Revilla Diez, J.

2012-08-01

The tsunami of December 2004 impacted large areas of Thailand's coastline and caused severe human and economic losses. The recovery period revealed differences in the vulnerabilities of communities affected. An understanding of the causal factors of vulnerability is crucial for minimising the negative effects of future threats and developing adaptive capacities. This paper analyses the vulnerabilities and the development of adaptation strategies in the booming tourist area of Khao Lak and in the predominantly fishing and agricultural area of Ban Nam Khem through a comprehensive vulnerability framework. The results show that social networks played a crucial role in coping with the disaster. Social cohesion is important for strengthening the community and developing successful adaptation strategies. The development of tourism and the turning away from traditional activities have a significant positive influence on the income situation, but create a dependency on a single business sector. It could be shown that households generating their income in the tourism sector were vulnerable unless they had diversified their income previously. Income diversification decreased the vulnerability in the study areas. Adaptation strategies and processes developed in the aftermath clearly address these issues.

Full-Scale Flight Research Testbeds: Adaptive and Intelligent Control

NASA Technical Reports Server (NTRS)

Pahle, Joe W.

2008-01-01

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

Adaptive Training of Manual Control: 1. Comparison of Three Adaptive Variables and Two Logic Schemes.

ERIC Educational Resources Information Center

Norman, D. A.; And Others

"Machine controlled adaptive training is a promising concept. In adaptive training the task presented to the trainee varies as a function of how well he performs. In machine controlled training, adaptive logic performs a function analogous to that performed by a skilled operator." This study looks at the ways in which gain-effective time…

Linear and non-linear systems identification for adaptive control in mechanical applications vibration suppression

NASA Astrophysics Data System (ADS)

Cazzulani, Gabriele; Resta, Ferruccio; Ripamonti, Francesco

2012-04-01

During the last years, more and more mechanical applications saw the introduction of active control strategies. In particular, the need of improving the performances and/or the system health is very often associated to vibration suppression. This goal can be achieved considering both passive and active solutions. In this sense, many active control strategies have been developed, such as the Independent Modal Space Control (IMSC) or the resonant controllers (PPF, IRC, . . .). In all these cases, in order to tune and optimize the control strategy, the knowledge of the system dynamic behaviour is very important and it can be achieved both considering a numerical model of the system or through an experimental identification process. Anyway, dealing with non-linear or time-varying systems, a tool able to online identify the system parameters becomes a key-point for the control logic synthesis. The aim of the present work is the definition of a real-time technique, based on ARMAX models, that estimates the system parameters starting from the measurements of piezoelectric sensors. These parameters are returned to the control logic, that automatically adapts itself to the system dynamics. The problem is numerically investigated considering a carbon-fiber plate model forced through a piezoelectric patch.

Recruitment of hard-to-reach population subgroups via adaptations of the snowball sampling strategy.

PubMed

Sadler, Georgia Robins; Lee, Hau-Chen; Lim, Rod Seung-Hwan; Fullerton, Judith

2010-09-01

Nurse researchers and educators often engage in outreach to narrowly defined populations. This article offers examples of how variations on the snowball sampling recruitment strategy can be applied in the creation of culturally appropriate, community-based information dissemination efforts related to recruitment to health education programs and research studies. Examples from the primary author's program of research are provided to demonstrate how adaptations of snowball sampling can be used effectively in the recruitment of members of traditionally underserved or vulnerable populations. The adaptation of snowball sampling techniques, as described in this article, helped the authors to gain access to each of the more-vulnerable population groups of interest. The use of culturally sensitive recruitment strategies is both appropriate and effective in enlisting the involvement of members of vulnerable populations. Adaptations of snowball sampling strategies should be considered when recruiting participants for education programs or for research studies when the recruitment of a population-based sample is not essential.

Target of physiological gait: Realization of speed adaptive control for a prosthetic knee during swing flexion.

PubMed

Cao, Wujing; Yu, Hongliu; Zhao, Weiliang; Li, Jin; Wei, Xiaodong

2018-01-01

Prosthetic knee is the most important component of lower limb prosthesis. Speed adaptive for prosthetic knee during swing flexion is the key method to realize physiological gait. This study aims to discuss the target of physiological gait, propose a speed adaptive control method during swing flexion and research the damping adjustment law of intelligent hydraulic prosthetic knee. According to the physiological gait trials of healthy people, the control target during swing flexion is defined. A new prosthetic knee with fuzzy logical control during swing flexion is designed to realize the damping adjustment automatically. The function simulation and evaluation system of intelligent knee prosthesis is provided. Speed adaptive control test of the intelligent prosthetic knee in different velocities are researched. The maximum swing flexion of the knee angle is set between sixty degree and seventy degree as the target of physiological gait. Preliminary experimental results demonstrate that the prosthetic knee with fuzzy logical control is able to realize physiological gait under different speeds. The faster the walking, the bigger the valve closure percentage of the hydraulic prosthetic knee. The proposed fuzzy logical control strategy and intelligent hydraulic prosthetic knee are effective for the amputee to achieve physiological gait.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2017-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2016-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered-reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

An adaptive control scheme for a flexible manipulator

NASA Technical Reports Server (NTRS)

Yang, T. C.; Yang, J. C. S.; Kudva, P.

1987-01-01

The problem of controlling a single link flexible manipulator is considered. A self-tuning adaptive control scheme is proposed which consists of a least squares on-line parameter identification of an equivalent linear model followed by a tuning of the gains of a pole placement controller using the parameter estimates. Since the initial parameter values for this model are assumed unknown, the use of arbitrarily chosen initial parameter estimates in the adaptive controller would result in undesirable transient effects. Hence, the initial stage control is carried out with a PID controller. Once the identified parameters have converged, control is transferred to the adaptive controller. Naturally, the relevant issues in this scheme are tests for parameter convergence and minimization of overshoots during control switch-over. To demonstrate the effectiveness of the proposed scheme, simulation results are presented with an analytical nonlinear dynamic model of a single link flexible manipulator.

Dynamics modeling and adaptive control of flexible manipulators

NASA Technical Reports Server (NTRS)

Sasiadek, J. Z.

1991-01-01

An application of Model Reference Adaptive Control (MRAC) to the position and force control of flexible manipulators and robots is presented. A single-link flexible manipulator is analyzed. The problem was to develop a mathematical model of a flexible robot that is accurate. The objective is to show that the adaptive control works better than 'conventional' systems and is suitable for flexible structure control.

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.

State-space self-tuner for on-line adaptive control

NASA Technical Reports Server (NTRS)

Shieh, L. S.

1994-01-01

Dynamic systems, such as flight vehicles, satellites and space stations, operating in real environments, constantly face parameter and/or structural variations owing to nonlinear behavior of actuators, failure of sensors, changes in operating conditions, disturbances acting on the system, etc. In the past three decades, adaptive control has been shown to be effective in dealing with dynamic systems in the presence of parameter uncertainties, structural perturbations, random disturbances and environmental variations. Among the existing adaptive control methodologies, the state-space self-tuning control methods, initially proposed by us, are shown to be effective in designing advanced adaptive controllers for multivariable systems. In our approaches, we have embedded the standard Kalman state-estimation algorithm into an online parameter estimation algorithm. Thus, the advanced state-feedback controllers can be easily established for digital adaptive control of continuous-time stochastic multivariable systems. A state-space self-tuner for a general multivariable stochastic system has been developed and successfully applied to the space station for on-line adaptive control. Also, a technique for multistage design of an optimal momentum management controller for the space station has been developed and reported in. Moreover, we have successfully developed various digital redesign techniques which can convert a continuous-time controller to an equivalent digital controller. As a result, the expensive and unreliable continuous-time controller can be implemented using low-cost and high performance microprocessors. Recently, we have developed a new hybrid state-space self tuner using a new dual-rate sampling scheme for on-line adaptive control of continuous-time uncertain systems.

Disturbance Accommodating Adaptive Control with Application to Wind Turbines

NASA Technical Reports Server (NTRS)

Frost, Susan

2012-01-01

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

Compromise-based Robust Prioritization of Climate Change Adaptation Strategies for Watershed Management

NASA Astrophysics Data System (ADS)

Kim, Y.; Chung, E. S.

2014-12-01

This study suggests a robust prioritization framework for climate change adaptation strategies under multiple climate change scenarios with a case study of selecting sites for reusing treated wastewater (TWW) in a Korean urban watershed. The framework utilizes various multi-criteria decision making techniques, including the VIKOR method and the Shannon entropy-based weights. In this case study, the sustainability of TWW use is quantified with indicator-based approaches with the DPSIR framework, which considers both hydro-environmental and socio-economic aspects of the watershed management. Under the various climate change scenarios, the hydro-environmental responses to reusing TWW in potential alternative sub-watersheds are determined using the Hydrologic Simulation Program in Fortran (HSPF). The socio-economic indicators are obtained from the statistical databases. Sustainability scores for multiple scenarios are estimated individually and then integrated with the proposed approach. At last, the suggested framework allows us to prioritize adaptation strategies in a robust manner with varying levels of compromise between utility-based and regret-based strategies.

Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

2016-01-01

Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

Decentralized adaptive control designs and microstrip antennas for smart structures

NASA Astrophysics Data System (ADS)

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

1996-05-01

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

Self-Tuning Adaptive-Controller Using Online Frequency Identification

NASA Technical Reports Server (NTRS)

Chiang, W. W.; Cannon, R. H., Jr.

1985-01-01

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Novel strategies in feedforward adaptation to a position-dependent perturbation.

PubMed

Hinder, Mark R; Milner, Theodore E

2005-08-01

To investigate the control mechanisms used in adapting to position-dependent forces, subjects performed 150 horizontal reaching movements over 25 cm in the presence of a position-dependent parabolic force field (PF). The PF acted only over the first 10 cm of the movement. On every fifth trial, a virtual mechanical guide (double wall) constrained subjects to move along a straight-line path between the start and target positions. Its purpose was to register lateral force to track formation of an internal model of the force field, and to look for evidence of possible alternative adaptive strategies. The force field produced a force to the right, which initially caused subjects to deviate in that direction. They reacted by producing deviations to the left, "into" the force field, as early as the second trial. Further adaptation resulted in rapid exponential reduction of kinematic error in the latter portion of the movement, where the greatest perturbation to the handpath was initially observed, whereas there was little modification of the handpath in the region where the PF was active. Significant force directed to counteract the PF was measured on the first guided trial, and was modified during the first half of the learning set. The total force impulse in the region of the PF increased throughout the learning trials, but it always remained less than that produced by the PF. The force profile did not resemble a mirror image of the PF in that it tended to be more trapezoidal than parabolic in shape. As in previous studies of force-field adaptation, we found that changes in muscle activation involved a general increase in the activity of all muscles, which increased arm stiffness, and selectively-greater increases in the activation of muscles which counteracted the PF. With training, activation was exponentially reduced, albeit more slowly than kinematic error. Progressive changes in kinematics and EMG occurred predominantly in the region of the workspace beyond the

Real-time control of geometry and stiffness in adaptive structures

NASA Technical Reports Server (NTRS)

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

1991-01-01

The basic theory is presented for the geometry, stiffness, and damping control of adaptive structures, with emphasis on adaptive truss structures. Necessary and sufficient conditions are given for stress-free geometry control in statically determinate and indeterminate adaptive discrete structures. Two criteria for selecting the controls are proposed, and their use in real-time control is illustrated by numerical simulation results. It is shown that the stiffness and damping control of adaptive truss structures for vibration suppression is possible by elongation and elongation rate dependent feedback forces from the active elements.

A comparison of two adaptive algorithms for the control of active engine mounts

NASA Astrophysics Data System (ADS)

Hillis, A. J.; Harrison, A. J. L.; Stoten, D. P.

2005-08-01

This paper describes work conducted in order to control automotive active engine mounts, consisting of a conventional passive mount and an internal electromagnetic actuator. Active engine mounts seek to cancel the oscillatory forces generated by the rotation of out-of-balance masses within the engine. The actuator generates a force dependent on a control signal from an algorithm implemented with a real-time DSP. The filtered-x least-mean-square (FXLMS) adaptive filter is used as a benchmark for comparison with a new implementation of the error-driven minimal controller synthesis (Er-MCSI) adaptive controller. Both algorithms are applied to an active mount fitted to a saloon car equipped with a four-cylinder turbo-diesel engine, and have no a priori knowledge of the system dynamics. The steady-state and transient performance of the two algorithms are compared and the relative merits of the two approaches are discussed. The Er-MCSI strategy offers significant computational advantages as it requires no cancellation path modelling. The Er-MCSI controller is found to perform in a fashion similar to the FXLMS filter—typically reducing chassis vibration by 50-90% under normal driving conditions.

RNA interference: a new strategy in the evolutionary arms race between human control strategies and insect pests.

PubMed

Machado, Vilmar; Rodríguez-García, María Juliana; Sánchez-García, Francisco Javier; Galan, Jose

2014-01-01

The relationship between humans and the insect pests of cultivated plants may be considered to be an indirect coevolutionary process, i.e., an arms race. Over time, humans have developed several strategies to minimize the negative impacts of insects on agricultural production. However, insects have made adaptive responses via the evolution of resistance to insecticides, and more recently against Bacillus thuriengiensis. Thus, we need to continuously invest resources in the development of new strategies for crop protection. Recent advances in genomics have demonstrated the possibility of a new weapon or strategy in this war, i.e., gene silencing, which involves blocking the expression of specific genes via mRNA inactivation. In the last decade, several studies have demonstrated the effectiveness of this strategy in the control of different species of insects. However, several technical difficulties need to be overcome to transform this potential into reality, such as the selection of target genes, the concentration of dsRNA, the nucleotide sequence of the dsRNA, the length of dsRNA, persistence in the insect body, and the life stage of the target species where gene silencing is most efficient. This study analyzes several aspects related to the use of gene silencing in pest control and it includes an overview of the inactivation process, as well as the problems that need to be resolved to transform gene silencing into an effective pest control method.

Strategies for informed sample size reduction in adaptive controlled clinical trials

NASA Astrophysics Data System (ADS)

Arandjelović, Ognjen

2017-12-01

Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. The main goal is to make the process of introducing new medical interventions to patients more efficient. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper, we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment, i.e. by reducing the number of trial participants in a statistically informed manner. Our key idea is to select the sample subset for removal in a manner which minimizes the associated loss of information. We formalize this notion and describe three algorithms which approach the problem in different ways, respectively, using (i) repeated random draws, (ii) a genetic algorithm, and (iii) what we term pair-wise sample compatibilities. Experiments on simulated data demonstrate the effectiveness of all three approaches, with a consistently superior performance exhibited by the pair-wise sample compatibilities-based method.

Control strategies for wind farm power optimization: LES study

NASA Astrophysics Data System (ADS)

Ciri, Umberto; Rotea, Mario; Leonardi, Stefano

2017-11-01

Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

NASA Astrophysics Data System (ADS)

Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

2016-04-01

Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Actuator placement in prestressed adaptive trusses for vibration control

NASA Technical Reports Server (NTRS)

Jalihal, P.; Utku, Senol; Wada, Ben K.

1993-01-01

This paper describes the optimal location selection of actuators for vibration control in prestressed adaptive trusses. Since prestressed adaptive trusses are statically indeterminate, the actuators to be used for vibration control purposes must work against (1) existing static axial prestressing forces, (2) static axial forces caused by the actuation, and (3) dynamic axial forces caused by the motion of the mass. In statically determinate adaptive trusses (1) and (2) are non - existing. The actuator placement problem in statically indeterminate trusses is therefore governed by the actuation energy and the actuator strength requirements. Assuming output feedback type control of selected vibration modes in autonomous systems, a procedure is given for the placement of vibration controlling actuators in prestressed adaptive trusses.

Stakeholders' participatory diagnosis of climate change impacts on subsistence agriculture in Sikkim, India, for identifying adaptation strategies

NASA Astrophysics Data System (ADS)

Azhoni, A.; Goyal, M. K.

2017-12-01

Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact subsistence agriculture. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers and perspectives of consultants and researchers which are expected to be implemented by development agencies farmers in the state of Sikkim in India. Our case study examined the framing and implementation of State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the State Government, Scientific Organisations, consultants, local academia, implementing and development agencies, and farmers for whom the adaptation strategies are targeted. Using Social Network and Stakeholder Analysis approach, this research unravels the complexities of perceiving climate change impacts, identifying adaptation strategies, and implementing climate change adaptation strategies. While farmers are less aware about the global phenomenon of climate change impacts for their subsistence livelihood, their knowledge of the local conditions and their close interaction with the State Government Agriculture Department provides them an access to new and high value crops. Although important steps are initiated through the Sikkim State Action Plan on Climate Change it is yet to deliver effective means of adaptation implementation and identifying the networks of close coordination between the various implementing agencies will likely to pay rich dividends. While Sikkim being a small and hilly state with specific contextual challenges of climate change impacts, the results from this study highlights how the internal and external networks between various types of stakeholders informs decision makers in identifying local impacts of climate change and plan adaptation strategies.

Trifocal Tensor-Based Adaptive Visual Trajectory Tracking Control of Mobile Robots.

PubMed

Chen, Jian; Jia, Bingxi; Zhang, Kaixiang

2017-11-01

In this paper, a trifocal tensor-based approach is proposed for the visual trajectory tracking task of a nonholonomic mobile robot equipped with a roughly installed monocular camera. The desired trajectory is expressed by a set of prerecorded images, and the robot is regulated to track the desired trajectory using visual feedback. Trifocal tensor is exploited to obtain the orientation and scaled position information used in the control system, and it works for general scenes owing to the generality of trifocal tensor. In the previous works, the start, current, and final images are required to share enough visual information to estimate the trifocal tensor. However, this requirement can be easily violated for perspective cameras with limited field of view. In this paper, key frame strategy is proposed to loosen this requirement, extending the workspace of the visual servo system. Considering the unknown depth and extrinsic parameters (installing position of the camera), an adaptive controller is developed based on Lyapunov methods. The proposed control strategy works for almost all practical circumstances, including both trajectory tracking and pose regulation tasks. Simulations are made based on the virtual experimentation platform (V-REP) to evaluate the effectiveness of the proposed approach.

Dosimetric evaluation of three adaptive strategies for prostate cancer treatment including pelvic lymph nodes irradiation

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

Cantin, Audrey; Gingras, Luc; Archambault, Louis, E-mail: louis.archambault@phy.ulaval.ca

Purpose: The movements of the prostate relative to the pelvic lymph nodes during intensity-modulated radiation therapy treatment can limit margin reduction and affect the protection of the organs at risk (OAR). In this study, the authors performed an analysis of three adaptive treatment strategies that combine information from both bony and gold marker registrations. The robustness of those treatments against the interfraction prostate movements was evaluated. Methods: A retrospective study was conducted on five prostate cancer patients with 7–13 daily cone-beam CTs (CBCTs). The clinical target volumes (CTVs) consisting of pelvic lymph nodes, prostate, and seminal vesicles as well asmore » the OARs were delineated on each CBCT and the initial CT. Three adaptive strategies were analyzed. Two of these methods relied on a two-step patient positioning at each fraction. First step: a bony registration was used to deliver the nodal CTV prescription. Second step: a gold marker registration was then used either to (1) complete the dose delivered to the prostate (complement); (2) or give almost the entire prescription to the prostate with a weak dose gradient between the targets to compensate for possible motions (gradient). The third method (COR) used a pool of precalculated plans based on images acquired at previous treatment fractions. At each new fraction, a plan is selected from that pool based on the daily position of prostate center-of-mass. The dosimetric comparison was conducted and results are presented with and without the systematic shift in the prostate position on the CT planning. The adaptive strategies were compared to the current clinical standard where all fractions are treated with the initial nonadaptive plan. Results: The minimum daily prostate D{sub 95%} is improved by 2%, 9%, and 6% for the complement, the gradient, and the COR approaches, respectively, compared to the nonadaptive method. The average nodal CTV D{sub 95%} remains constant across

Dosimetric evaluation of three adaptive strategies for prostate cancer treatment including pelvic lymph nodes irradiation.

PubMed

Cantin, Audrey; Gingras, Luc; Lachance, Bernard; Foster, William; Goudreault, Julie; Archambault, Louis

2015-12-01

The movements of the prostate relative to the pelvic lymph nodes during intensity-modulated radiation therapy treatment can limit margin reduction and affect the protection of the organs at risk (OAR). In this study, the authors performed an analysis of three adaptive treatment strategies that combine information from both bony and gold marker registrations. The robustness of those treatments against the interfraction prostate movements was evaluated. A retrospective study was conducted on five prostate cancer patients with 7-13 daily cone-beam CTs (CBCTs). The clinical target volumes (CTVs) consisting of pelvic lymph nodes, prostate, and seminal vesicles as well as the OARs were delineated on each CBCT and the initial CT. Three adaptive strategies were analyzed. Two of these methods relied on a two-step patient positioning at each fraction. First step: a bony registration was used to deliver the nodal CTV prescription. Second step: a gold marker registration was then used either to (1) complete the dose delivered to the prostate (complement); (2) or give almost the entire prescription to the prostate with a weak dose gradient between the targets to compensate for possible motions (gradient). The third method (COR) used a pool of precalculated plans based on images acquired at previous treatment fractions. At each new fraction, a plan is selected from that pool based on the daily position of prostate center-of-mass. The dosimetric comparison was conducted and results are presented with and without the systematic shift in the prostate position on the CT planning. The adaptive strategies were compared to the current clinical standard where all fractions are treated with the initial nonadaptive plan. The minimum daily prostate D95% is improved by 2%, 9%, and 6% for the complement, the gradient, and the COR approaches, respectively, compared to the nonadaptive method. The average nodal CTV D95% remains constant across the strategies, except for the gradient approach

Self-organizing radial basis function networks for adaptive flight control and aircraft engine state estimation

NASA Astrophysics Data System (ADS)

Shankar, Praveen

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network

Vibration control in statically indeterminate adaptive truss structures

NASA Technical Reports Server (NTRS)

Baycan, C. M.; Utku, Senol; Wada, Ben K.

1993-01-01

In this work vibration control of statically indeterminate adaptive truss structures is investigated. Here, the actuators (i.e., length adjusting devices) that are used for vibration control, work against the axial forces caused by the inertial forces. In statically determinate adaptive trusses no axial force is induced by the actuation. The control problem in statically indeterminate trusses may be dominated by the actuation-induced axial element forces. The creation of actuation-induced axial forces puts the system to a higher energy state, thus aggravates the controls. It is shown that by the usage of sufficient number of slave actuators in addition to the actual control actuators, the actuation-induced axial element forces can be nullified, and the control problem of the statically indeterminate adaptive truss problem is reduced to that of a statically determinate one. It is also shown that the usage of slave actuators saves a great amount of control energy and provides robustness for the controls.

Adaptive control of artificial pancreas systems - a review.

PubMed

Turksoy, Kamuran; Cinar, Ali

2014-01-01

Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.

Mixed-Strategy Chance Constrained Optimal Control

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.

2013-01-01

This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

Control strategies for effective robot assisted gait rehabilitation: the state of art and future prospects.