Salden, Ron; Paas, Fred; Van Merriënboer, Jeroen
Salden, R.J.C.M., Paas, F., & Van Merriënboer, J.J.G. (2006). Personalised adaptive task selection in air traffic control: Effects on training efficiency and transfer. Learning and Instruction, 16, 350-362
Adams, Samantha V; Wennekers, Thomas; Denham, Sue; Culverhouse, Phil F
This work investigates self-organising cortical feature maps (SOFMs) based upon the Kohonen Self-Organising Map (SOM) but implemented with spiking neural networks. In future work, the feature maps are intended as the basis for a sensorimotor controller for an autonomous humanoid robot. Traditional SOM methods require some modifications to be useful for autonomous robotic applications. Ideally the map training process should be self-regulating and not require predefined training files or the usual SOM parameter reduction schedules. It would also be desirable if the organised map had some flexibility to accommodate new information whilst preserving previous learnt patterns. Here methods are described which have been used to develop a cortical motor map training system which goes some way towards addressing these issues. The work is presented under the general term 'Adaptive Plasticity' and the main contribution is the development of a 'plasticity resource' (PR) which is modelled as a global parameter which expresses the rate of map development and is related directly to learning on the afferent (input) connections. The PR is used to control map training in place of a traditional learning rate parameter. In conjunction with the PR, random generation of inputs from a set of exemplar patterns is used rather than predefined datasets and enables maps to be trained without deciding in advance how much data is required. An added benefit of the PR is that, unlike a traditional learning rate, it can increase as well as decrease in response to the demands of the input and so allows the map to accommodate new information when the inputs are changed during training.
Full Text Available Abstract Background In the last two decades robot training in neuromotor rehabilitation was mainly focused on shoulder-elbow movements. Few devices were designed and clinically tested for training coordinated movements of the wrist, which are crucial for achieving even the basic level of motor competence that is necessary for carrying out ADLs (activities of daily life. Moreover, most systems of robot therapy use point-to-point reaching movements which tend to emphasize the pathological tendency of stroke patients to break down goal-directed movements into a number of jerky sub-movements. For this reason we designed a wrist robot with a range of motion comparable to that of normal subjects and implemented a self-adapting training protocol for tracking smoothly moving targets in order to facilitate the emergence of smoothness in the motor control patterns and maximize the recovery of the normal RoM (range of motion of the different DoFs (degrees of Freedom. Methods The IIT-wrist robot is a 3 DoFs light exoskeleton device, with direct-drive of each DoF and a human-like range of motion for Flexion/Extension (FE, Abduction/Adduction (AA and Pronation/Supination (PS. Subjects were asked to track a variable-frequency oscillating target using only one wrist DoF at time, in such a way to carry out a progressive splinting therapy. The RoM of each DoF was angularly scanned in a staircase-like fashion, from the "easier" to the "more difficult" angular position. An Adaptive Controller evaluated online performance parameters and modulated both the assistance and the difficulty of the task in order to facilitate smoother and more precise motor command patterns. Results Three stroke subjects volunteered to participate in a preliminary test session aimed at verify the acceptability of the device and the feasibility of the designed protocol. All of them were able to perform the required task. The wrist active RoM of motion was evaluated for each patient at the
van Dam, K.G.
It appears that the physiological and biochemical adaptation of skeletal muscle to training in equine species shows a lot of similarities with human and rodent physiological adaptation. On the other hand it is becoming increasingly clear that intra-cellular mechanisms of adaptation (substrate transport, enzyme activity, etc) differ considerably between species. The major drawbacks in equine training physiological research are the lack of an appropriate training model and the lack of control o...
Full Text Available Muscle strength training for stroke patients is of vital importance for helping survivors to progressively restore muscle strength and improve the performance of their activities in daily living (ADL. An adaptive hierarchical therapy control framework which integrates the patient’s real biomechanical state estimation with task‐performance quantitative evaluation is proposed. Firstly, a high‐level progressive resistive supervisory controller is designed to determine the resistive force base for each training session based on the patient’s online task‐performance evaluation. Then, a low‐level adaptive resistive force triggered controller is presented to further regulate the interactive resistive force corresponding to the patient’s real‐time biomechanical state ‐ characterized by the patient’s bio‐damping and bio‐stiffness in the course of one training session, so that the patient is challenged in a moderate but engaging and motivating way. Finally, a therapeutic robot system using a Barrett WAMTM compliant manipulator is set up. We recruited eighteen inpatient and outpatient stroke participants who were randomly allocated in experimental (robot‐aided and control (conventional physical therapy groups and enrolled for sixteen weeks of progressive resistance training. The preliminary results show that the proposed therapy control strategies can enhance the recovery of strength and motor control ability.
Rivera, Iris Daliz
The field of training has been changing rapidly due to advances in technology such as videogame-based adaptive training. Videogame-based adaptive training has provided flexibility and adaptability for training in cost-effective ways. Although this method of training may have many benefits for the trainee, current research has not kept up to pace…
He, Jiayuan; Zhang, Dingguo; Jiang, Ning; Sheng, Xinjun; Farina, Dario; Zhu, Xiangyang
Objective. Recent studies have reported that the classification performance of electromyographic (EMG) signals degrades over time without proper classification retraining. This problem is relevant for the applications of EMG pattern recognition in the control of active prostheses. Approach. In this study we investigated the changes in EMG classification performance over 11 consecutive days in eight able-bodied subjects and two amputees. Main results. It was observed that, when the classifier was trained on data from one day and tested on data from the following day, the classification error decreased exponentially but plateaued after four days for able-bodied subjects and six to nine days for amputees. The between-day performance became gradually closer to the corresponding within-day performance. Significance. These results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased. The performance of the motor tasks is thus more consistent over time, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance. The learning curves for both able-bodied subjects and subjects with limb deficiencies could be modeled as an exponential function. These results provide important insights into the user adaptation characteristics during practical long-term myoelectric control applications, with implications for the design of an adaptive pattern recognition system.
Hellsten, Ylva; Nyberg, Michael
Aerobic exercise training leads to cardiovascular changes that markedly increase aerobic power and lead to improved endurance performance. The functionally most important adaptation is the improvement in maximal cardiac output which is the result of an enlargement in cardiac dimension, improved...... arteries is reduced, a factor contributing to increased arterial compliance. Endurance training may also induce alterations in the vasodilator capacity, although such adaptations are more pronounced in individuals with reduced vascular function. The microvascular net increases in size within the muscle...... allowing for an improved capacity for oxygen extraction by the muscle through a greater area for diffusion, a shorter diffusion distance, and a longer mean transit time for the erythrocyte to pass through the smallest blood vessels. The present article addresses the effect of endurance training on systemic...
Full Text Available Current eye-tracking research suggests that our eyes make anticipatory movements to a location that is relevant for a forthcoming task. Moreover, there is evidence to suggest that with more practice anticipatory gaze control can improve. However, these findings are largely limited to situations where participants are actively engaged in a task. We ask: does experience modulate anticipative gaze control while passively observing a visual scene? To tackle this we tested people with varying degrees of experience of tennis, in order to uncover potential associations between experience and eye movement behaviour while they watched tennis videos. The number, size, and accuracy of saccades (rapid eye-movements made around 'events,' which is critical for the scene context (i.e. hit and bounce were analysed. Overall, we found that experience improved anticipatory eye-movements while watching tennis clips. In general, those with extensive experience showed greater accuracy of saccades to upcoming event locations; this was particularly prevalent for events in the scene that carried high uncertainty (i.e. ball bounces. The results indicate that, even when passively observing, our gaze control system utilizes prior relevant knowledge in order to anticipate upcoming uncertain event locations.
Maffiuletti, Nicola A; Zory, Raphael; Miotti, Danilo; Pellegrino, Maria A; Jubeau, Marc; Bottinelli, Roberto
A combination of in vivo and in vitro analyses was performed to investigate muscular and neural adaptations of the weaker (nondominant) quadriceps femoris muscle of one healthy individual to short-term electrostimulation resistance training. The increase in maximal voluntary strength (+12%) was accompanied by neural (cross-education effect and increased muscle activation) and muscle adaptations (impairment of whole-muscle contractile properties). Significant changes in myosin heavy chain (MHC) isoforms relative content (+22% for MHC-2A and -28% for MHC-2X), single-fiber cross-sectional area (+27% for type 1 and +6% for type 2A muscle fibers), and specific tension of type 1 (+67%) but not type 2A fibers were also observed after training. Plastic changes in neural control confirm the possible involvement of both spinal and supraspinal structures to electrically evoked contractions. Changes at the single muscle fiber level induced by electrostimulation resistance training were significant and preferentially affected slow, type 1 fibers.
Kaminski, Lois Anne
Exercise training causes physiological changes in skeletal muscle that results in enhanced performance in humans and animals. Despite numerous studies on exercise effects on skeletal muscle, relatively little is known about adaptive changes in the central nervous system. This study investigated whether spinal pathways that mediate locomotor activity undergo functional adaptation after 28 days of exercise training. Ventral horn spinal cord expression of calcitonin gene-related peptide (CGRP), a trophic factor at the neuromuscular junction, choline acetyltransferase (Chat), the synthetic enzyme for acetylcholine, vesicular acetylcholine transporter (Vacht), a transporter of ACh into synaptic vesicles and calcineurin (CaN), a protein phosphatase that phosphorylates ion channels and exocytosis machinery were measured to determine if changes in expression occurred in response to physical activity. Expression of these proteins was determined by western blot and immunohistochemistry (IHC). Comparisons between sedentary controls and animals that underwent either endurance training or resistance training were made. Control rats received no exercise other than normal cage activity. Endurance-trained rats were exercised 6 days/wk at 31m/min on a treadmill (8% incline) for 100 minutes. Resistance-trained rats supported their weight plus an additional load (70--80% body weight) on a 60° incline (3 x 3 min, 5 days/wk). CGRP expression was measured by radioimmunoassay (RIA). CGRP expression in the spinal dorsal and ventral horn of exercise-trained animals was not significantly different than controls. Chat expression measured by Western blot and IHC was not significantly different between runners and controls but expression in resistance-trained animals assayed by IHC was significantly less than controls and runners. Vacht and CaN immunoreactivity in motor neurons of endurance-trained rats was significantly elevated relative to control and resistance-trained animals. Ventral
Mujika, Iñigo; Stellingwerff, Trent; Tipton, Kevin
The adaptive response to training is determined by the combination of the intensity, volume, and frequency of the training. Various periodized approaches to training are used by aquatic sports athletes to achieve performance peaks. Nutritional support to optimize training adaptations should take periodization into consideration; that is, nutrition should also be periodized to optimally support training and facilitate adaptations. Moreover, other aspects of training (e.g., overload training, tapering and detraining) should be considered when making nutrition recommendations for aquatic athletes. There is evidence, albeit not in aquatic sports, that restricting carbohydrate availability may enhance some training adaptations. More research needs to be performed, particularly in aquatic sports, to determine the optimal strategy for periodizing carbohydrate intake to optimize adaptations. Protein nutrition is an important consideration for optimal training adaptations. Factors other than the total amount of daily protein intake should be considered. For instance, the type of protein, timing and pattern of protein intake and the amount of protein ingested at any one time influence the metabolic response to protein ingestion. Body mass and composition are important for aquatic sport athletes in relation to power-to-mass and for aesthetic reasons. Protein may be particularly important for athletes desiring to maintain muscle while losing body mass. Nutritional supplements, such as b-alanine and sodium bicarbonate, may have particular usefulness for aquatic athletes' training adaptation.
Narendra, K. S.; Annaswamy, A. M.
Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.
Yang, Chi-Ming; Beck, James L.
A new robust adaptive structural control design methodology is developed and presented which treats modeling uncertainties and limitations of control devices. Furthermore, no restriction is imposed on the structural models and the nature of the control devices so that the proposed method is very general. A simple linear single degree-of-freedom numerical example is presented to illustrate this approach.
Dam, K.G. van
It appears that the physiological and biochemical adaptation of skeletal muscle to training in equine species shows a lot of similarities with human and rodent physiological adaptation. On the other hand it is becoming increasingly clear that intra-cellular mechanisms of adaptation (substrate transp
Hortobagyi, Tibor; Maffiuletti, Nicola A.
This review provides evidence for the hypothesis that electrostimulation strength training (EST) increases the force of a maximal voluntary contraction (MVC) through neural adaptations in healthy skeletal muscle. Although electrical stimulation and voluntary effort activate muscle differently, there
Alkjær, Tine; Meyland, Jacob; Raffalt, Peter C;
This study examined the effects of 4 weeks of intensive drop jump training in well-trained athletes on jumping performance and underlying changes in biomechanics and neuromuscular adaptations. Nine well-trained athletes at high national competition level within sprinting and jumping disciplines...... performance also in well-trained athletes without concomitant changes in muscle strength. It is suggested that the behavioral improvement is primarily due to neural factors regulating the activation pattern controlling the drop jump movement....
Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V
This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Abbott, Robert G.; Forsythe, James C.
Adaptive Thinking has been defined here as the capacity to recognize when a course of action that may have previously been effective is no longer effective and there is need to adjust strategy. Research was undertaken with human test subjects to identify the factors that contribute to adaptive thinking. It was discovered that those most effective in settings that call for adaptive thinking tend to possess a superior capacity to quickly and effectively generate possible courses of action, as measured using the Category Generation test. Software developed for this research has been applied to develop capabilities enabling analysts to identify crucial factors that are predictive of outcomes in fore-on-force simulation exercises.
Schreuder, T.H.A.; Green, D.J.; Nyakayiru, J.; Hopman, M.T.E.; Thijssen, D.H.J.
PURPOSE: Exercise training in healthy volunteers rapidly improves vascular function, preceding structural remodelling. No study examined the time-course of such adaptations in subjects with a priori endothelial dysfunction. METHODS: We examined brachial artery endothelial and smooth muscle function
National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...
Ray, C. A.
The purpose of the present study was to determine the effect of leg exercise training on sympathetic nerve responses at rest and during dynamic exercise. Six men were trained by using high-intensity interval and prolonged continuous one-legged cycling 4 day/wk, 40 min/day, for 6 wk. Heart rate, mean arterial pressure (MAP), and muscle sympathetic nerve activity (MSNA; peroneal nerve) were measured during 3 min of upright dynamic one-legged knee extensions at 40 W before and after training. After training, peak oxygen uptake in the trained leg increased 19 +/- 2% (P training (108 +/- 5 to 96 +/- 5 beats/min and 132 +/- 8 to 119 +/- 4 mmHg, respectively, during the third minute of exercise; P training. However, MSNA was significantly less during the third minute of exercise after training (32 +/- 2 to 22 +/- 3 bursts/min; P training effect on MSNA remained when MSNA was expressed as bursts per 100 heartbeats. Responses to exercise in five untrained control subjects were not different at 0 and 6 wk. These results demonstrate that exercise training prolongs the decrease in MSNA during upright leg exercise and indicates that attenuation of MSNA to exercise reported with forearm training also occurs with leg training.
Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang
Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.
Fernandez-Gonzalo, Rodrigo; Fernandez-Gonzalo, Sol; Turon, Marc; Prieto, Cristina; Tesch, Per A; García-Carreira, Maria del Carmen
Background Resistance exercise (RE) improves neuromuscular function and physical performance after stroke. Yet, the effects of RE emphasizing eccentric (ECC; lengthening) actions on muscle hypertrophy and cognitive function in stroke patients are currently unknown. Thus, this study explored the effects of ECC-overload RE training on skeletal muscle size and function, and cognitive performance in individuals with stroke. Methods Thirty-two individuals with chronic stroke (≥6 months post-stroke...
Goodwin, Graham C
Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o
Jacob J Bloomberg
Full Text Available Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments - enhancing their ability to learn to learn. We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts.
Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P
Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561
Keith, S P; Jacobs, I; McLellan, T M
The individual anaerobic threshold (Th(an)) is the highest metabolic rate at which blood lactate concentrations can be maintained at a steady-state during prolonged exercise. The purpose of this study was to test the hypothesis that training at the Th(an) would cause a greater change in indicators of training adaptation than would training "around" the Th(an). Three groups of subjects were evaluated before, and again after 4 and 8 weeks of training: a control group, a group which trained continuously for 30 min at the Th(an) intensity (SS), and a group (NSS) which divided the 30 min of training into 7.5-min blocks at intensities which alternated between being below the Th(an) [Th(an) -30% of the difference between Th(an) and maximal oxygen consumption (VO2max)] and above the Th(an) (Th(an) +30% of the difference between Th(an) and VO2max). The VO2max increased significantly from 4.06 to 4.27 l.min-1 in SS and from 3.89 to 4.06 l.min-1 in NSS. The power output (W) at Th(an) increased from 70.5 to 79.8% VO2max in SS and from 71.1 to 80.7% VO2max in NSS. The magnitude of change in VO2max, W at Th(an), % VO2max at Th(an) and in exercise time to exhaustion at the pretraining Th(an) was similar in both trained groups. Vastus lateralis citrate synthase and 3-hydroxyacyl-CoA-dehydrogenase activities increased to the same extent in both trained groups. While all of these training-induced adaptations were statistically significant (P < 0.05), there were no significant changes in any of these variables for the control subjects.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:1425631
Bickford, Randall L; Palnitkar, Rahul M; Lee, Vo
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
Bickford, Randall L; Palnitkar, Rahul M
An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.
Ciftcioglu, Oe. [Istanbul Technical Univ. (Turkey). Dept. of Electrical Engineering; Tuerkcan, E. [Netherlands Energy Research Foundation (ECN), Petten (Netherlands)
Adaptive training of feedforward neural networks by Kalman filtering is described. Adaptive training is particularly important in estimation by neural network in real-time environmental where the trained network is used for system estimation while the network is further trained by means of the information provided by the experienced/exercised ongoing operation. As result of this, neural network adapts itself to a changing environment to perform its mission without recourse to re-training. The performance of the training method is demonstrated by means of actual process signals from a nuclear power plant. (orig.).
Dr. P. Vijayakumar; UNNIKRISHNAN P C
In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR) to ensure stability of the system. The design involves a parallel feedforward compensator (PFC) which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizi...
Lei, Yuming; Bao, Shancheng; Wang, Jinsung
Sensorimotor adaptation can be induced by action observation, and also by passive training. Here, we investigated the effect of a protocol that combined action observation and passive training on visuomotor adaptation, by comparing it with the effect of action observation or passive training alone. Subjects were divided into five conditions during the training session: (1) action observation, in which the subjects watched a video of a model who adapted to a novel visuomotor rotation; (2) proprioceptive training, in which the subject's arm was moved passively to target locations that were associated with desired trajectories; (3) combined training, in which the subjects watched the video of a model during a half of the session and experienced passive movements during the other half; (4) active training, in which the subjects adapted actively to the rotation; and (5) a control condition, in which the subjects did not perform any task. Following that session, all subjects adapted to the same visuomotor rotation. Results showed that the subjects in the combined training condition adapted to the rotation significantly better than those in the observation or proprioceptive training condition, although their performance was not as good as that of those who adapted actively. These findings suggest that although a protocol that combines action observation and passive training consists of all the processes involved in active training (error detection and correction, effector-specific and proprioceptively based reaching movements), these processes in that protocol may work differently as compared to a protocol in which the same processes are engaged actively.
Lei, Yuming; Bao, Shancheng; Wang, Jinsung
Sensorimotor adaptation can be induced by action observation, and also by passive training. Here, we investigated the effect of a protocol that combined action observation and passive training on visuomotor adaptation, by comparing it with the effect of action observation or passive training alone. Subjects were divided into five conditions during the training session: (1) action observation, in which the subjects watched a video of a model who adapted to a novel visuomotor rotation; (2) proprioceptive training, in which the subject's arm was moved passively to target locations that were associated with desired trajectories; (3) combined training, in which the subjects watched the video of a model during a half of the session and experienced passive movements during the other half; (4) active training, in which the subjects adapted actively to the rotation; and (5) a control condition, in which the subjects did not perform any task. Following that session, all subjects adapted to the same visuomotor rotation. Results showed that the subjects in the combined training condition adapted to the rotation significantly better than those in the observation or proprioceptive training condition, although their performance was not as good as that of those who adapted actively. These findings suggest that although a protocol that combines action observation and passive training consists of all the processes involved in active training (error detection and correction, effector-specific and proprioceptively based reaching movements), these processes in that protocol may work differently as compared to a protocol in which the same processes are engaged actively. PMID:27298007
Yfanti, Christina; Åkerström, Thorbjörn; Nielsen, Søren;
BACKGROUND: There is a considerable commercial market, especially within the sports community, claiming the need for antioxidant supplementation. One argument for antioxidant supplementation in sports is that physical exercise is associated with increased reactive oxygen and nitrogen species (RONS......) production, which may cause cell damage. However, RONS production may also activate redox sensitive signaling pathways and transcription factors, which subsequently may promote training adaptation. PURPOSE: Our aim was to investigate the effects of combined vitamin C and E supplementation to healthy...... individuals on different measures of exercise performance after endurance training. METHODS:: Using a double-blinded placebo-controlled design, moderately trained young men received either oral supplementation with vitamins C and E (n=11) or placebo (n=10) before and during 12 weeks of supervised, strenuous...
This thesis is divided into two parts, i.e., adaptive extremum control and modelling and control of a wind turbine. The rst part of the thesis deals with the design of adaptive extremum controllers for some processes which have the behaviour that process should have as high e ciency as possible...... in parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important...... role. If it can be emphasis on control design. The models have beenvalidated by experimental data obtained from an existing wind turbine. The e ective wind speed experienced by the rotor of a wind turbine, which is often required by some control methods, is estimated by using a wind turbine as a wind...
DR. P VIJAYAKUMAR
Full Text Available In this paper an adaptive stable PID controller is briefly explained and validated by simulations and experimentation. The adaptive PID controller employs almost strict positive realness (ASPR to ensure stability of the system. The design involves a parallel feedforward compensator (PFC which guarantees the ASPRness of the controlled system. After a disturbance the dynamical system is assumed to be in one of a finite number of configurations, corresponding to each of which exist a stabilizing controller. The effectiveness of the method is tested and compared using simulations and experiments on a level control experimental setup.
ZHU Liye; FANG Yuan; ZHANG Weidong
According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.
Robust and adaptive control techniques have a rich history of theoretical development with successful application. Despite the accomplishments made, attempts to combine the best elements of each approach into robust adaptive systems has proven challenging, particularly in the area of application to real world aerospace systems. In this research, we investigate design methods for general classes of systems that may be applied to representative aerospace dynamics. By combining robust baseline control design with augmentation designs, our work aims to leverage the advantages of each approach. This research contributes the development of robust model-based control design for two classes of dynamics: 2nd order cascaded systems, and a more general MIMO framework. We present a theoretically justified method for state limiting via augmentation of a robust baseline control design. Through the development of adaptive augmentation designs, we are able to retain system performance in the presence of uncertainties. We include an extension that combines robust baseline design with both state limiting and adaptive augmentations. In addition we develop an adaptive augmentation design approach for a class of dynamic input uncertainties. We present formal stability proofs and analyses for all proposed designs in the research. Throughout the work, we present real world aerospace applications using relevant flight dynamics and flight test results. We derive robust baseline control designs with application to both piloted and unpiloted aerospace system. Using our developed methods, we add a flight envelope protecting state limiting augmentation for piloted aircraft applications and demonstrate the efficacy of our approach via both simulation and flight test. We illustrate our adaptive augmentation designs via application to relevant fixed-wing aircraft dynamics. Both a piloted example combining the state limiting and adaptive augmentation approaches, and an unpiloted example with
Nguyen, Nhan T.
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.
Brødsgaard, Kjeld Erik
Review of: Training the Party: Party Adaptation and Elite Training in Reform-era China. Charlotte P. Lee . Cambridge: Cambridge University Press, 2015. xii + 251 pp. $99.99. ISBN 978-1-107-09063-7......Review of: Training the Party: Party Adaptation and Elite Training in Reform-era China. Charlotte P. Lee . Cambridge: Cambridge University Press, 2015. xii + 251 pp. $99.99. ISBN 978-1-107-09063-7...
Ohtani, Yamato; Toda, Tomoki; Saruwatari, Hiroshi; Shikano, Kiyohiro
In this paper, we describe a novel model training method for one-to-many eigenvoice conversion (EVC). One-to-many EVC is a technique for converting a specific source speaker's voice into an arbitrary target speaker's voice. An eigenvoice Gaussian mixture model (EV-GMM) is trained in advance using multiple parallel data sets consisting of utterance-pairs of the source speaker and many pre-stored target speakers. The EV-GMM can be adapted to new target speakers using only a few of their arbitrary utterances by estimating a small number of adaptive parameters. In the adaptation process, several parameters of the EV-GMM to be fixed for different target speakers strongly affect the conversion performance of the adapted model. In order to improve the conversion performance in one-to-many EVC, we propose an adaptive training method of the EV-GMM. In the proposed training method, both the fixed parameters and the adaptive parameters are optimized by maximizing a total likelihood function of the EV-GMMs adapted to individual pre-stored target speakers. We conducted objective and subjective evaluations to demonstrate the effectiveness of the proposed training method. The experimental results show that the proposed adaptive training yields significant quality improvements in the converted speech.
Bottiroli, Sara; Cavallini, Elena; Dunlosky, John; Vecchi, Tomaso; Hertzog, Christopher
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.
Nyberg, Michael Permin; Fiorenza, Matteo; Lund, Anders;
PURPOSE: The present study examined whether a period of additional speed endurance training would improve intense intermittent exercise performance in highly trained soccer players during the season and whether the training changed aerobic metabolism and the level of oxidative enzymes in type I...... and II muscle fibers. METHODS: During the last nine weeks of the season, thirteen semi-professional soccer players performed additional speed endurance training sessions consisting of 2-3 sets of 8 - 10 repetitions of 30 m sprints with 10 s of passive recovery (SET). Before and after SET, subjects...... in type I and II fibers did not change. CONCLUSION: In highly trained soccer players, additional speed endurance training is associated with an improved ability to perform repeated high-intensity work. To what extent the training-induced changes in V˙O2 kinetics and mechanical efficiency in type I fibers...
Ethier, Christian; Acuna, Daniel; Solla, Sara A.; Miller, Lee E.
Objective. We have previously demonstrated a brain-machine interface neuroprosthetic system that provided continuous control of functional electrical stimulation (FES) and restoration of grasp in a primate model of spinal cord injury (SCI). Predicting intended EMG directly from cortical recordings provides a flexible high-dimensional control signal for FES. However, no peripheral signal such as force or EMG is available for training EMG decoders in paralyzed individuals. Approach. Here we present a method for training an EMG decoder in the absence of muscle activity recordings; the decoder relies on mapping behaviorally relevant cortical activity to the inferred EMG activity underlying an intended action. Monkeys were trained at a 2D isometric wrist force task to control a computer cursor by applying force in the flexion, extension, ulnar, and radial directions and execute a center-out task. We used a generic muscle force-to-endpoint force model based on muscle pulling directions to relate each target force to an optimal EMG pattern that attained the target force while minimizing overall muscle activity. We trained EMG decoders during the target hold periods using a gradient descent algorithm that compared EMG predictions to optimal EMG patterns. Main results. We tested this method both offline and online. We quantified both the accuracy of offline force predictions and the ability of a monkey to use these real-time force predictions for closed-loop cursor control. We compared both offline and online results to those obtained with several other direct force decoders, including an optimal decoder computed from concurrently measured neural and force signals. Significance. This novel approach to training an adaptive EMG decoder could make a brain-control FES neuroprosthesis an effective tool to restore the hand function of paralyzed individuals. Clinical implementation would make use of individualized EMG-to-force models. Broad generalization could be achieved by
WANG Guang-Li; HUANG Shi-Yong; ZHANG Ying-Ying; LIANG Pei-Ji
@@ The difference in temporal structures of retinal ganglion cell spike trains between spontaneous activity and firing activity after contrast adaptation is investigated. The Lempel-Ziv complexity analysis reveals that the complexity of the neural spike train decreases after contrast adaptation. This implies that the behaviour of the neuron becomes ordered, which may carry relevant information about the external stimulus. Thus, during the neuron activity after contrast adaptation, external information could be encoded in forms of some certain patterns in the temporal structure of spike train that is significantly different, compared to that of the spike train during spontaneous activity, although the firing rates in spontaneous activity and firing activity after contrast adaptation are sometime similar.
This manual defines and describes the DOE Radiological Control Technician Core Training Program qualification and training process, material development requirements, standards and policies, and administration. The manual applies to Radiological Control Technician Training Programs at all DOE contractor sites
Handelman, David A.
The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.
Arabatzi, Fotini; Kellis, Eleftherios
The purpose of this study was to compare the effects of an Olympic weightlifting (OL) and traditional weight (TW) training program on muscle coactivation around the knee joint during vertical jump tests. Twenty-six men were assigned randomly to 3 groups: the OL (n = 9), the TW (n = 9), and Control (C) groups (n = 8). The experimental groups trained 3 d · wk(-1) for 8 weeks. Electromyographic (EMG) activity from the rectus femoris and biceps femoris, sagittal kinematics, vertical stiffness, maximum height, and power were collected during the squat jump, countermovement jump (CMJ), and drop jump (DJ), before and after training. Knee muscle coactivation index (CI) was calculated for different phases of each jump by dividing the antagonist EMG activity by the agonist. Analysis of variance showed that the CI recorded during the preactivation and eccentric phases of all the jumps increased in both training groups. The OL group showed a higher stiffness and jump height adaptation than the TW group did (p knee, coupled with changes of leg stiffness, differ between the 2 programs. The OL program improves jump performance via a constant CI, whereas the TW training caused an increased CI, probably to enhance joint stability.
Hansen, Jens Peter; Ostergaard, Birte; Nordentoft, Merete;
Cognitive adaptation training (CAT) targets the adaptive behaviour of patients with schizophrenia and has shown promising results regarding the social aspects of psychosocial treatment. As yet, no reports have appeared on the use of CAT in combination with assertive community treatment (ACT). Our...
National Aeronautics and Space Administration — The ADEPT project aims to improve the state-of-the-art with respect to capabilities and costs of scenario-based training in support of future space exploration...
General neural network inverse adaptive controller haa two flaws: the first is the slow convergence speed; the second is the invalidation to the non-minimum phase system.These defects limit the scope in which the neural network inverse adaptive controller is used.We employ Davidon least squares in training the multi-layer feedforward neural network used in approximating the inverse model of plant to expedite the convergence,and then through constructing the pseudo-plant,a neural network inverse adaptive controller is put forward which is still effective to the nonlinear non-minimum phase system.The simulation results show the validity of this scheme.
Andersen, L L; Andersen, Jesper Løvind; Zebis, M K;
The objective of this study is to investigate the potentially opposing influence of qualitative and quantitative muscular adaptations in response to high-intensity resistance training on contractile rate of force development (RFD) in the early (200 ms) of rising muscle force. Fifteen healthy young......-intensity resistance training due to differential influences of qualitative and quantitative muscular adaptations on early and later phases of rising muscle force....... males participated in a 14-week resistance training intervention for the lower body and 10 matched subjects participated as controls. Maximal muscle strength (MVC) and RFD were measured during maximal voluntary isometric contraction of the quadriceps femoris muscle. Muscle biopsies were obtained from...
According to the observance of ELT （English Language Training）classes in China, the selection of reading materials becomes a big problem. Most teachers there are in a traditional way of following the textbooks, and regard texts given in those books as the sole resource of teaching materials. However, those texts are not ideal for all situations, and when there are problems, we need to make improvements instead of sticking to the authority of textbooks. In this paper the author will illustrate the necessity of adapting reading textbooks mainly in a Chinese ELT context and set forth some corresponding suggestions about adaption in differ- ent cases.
Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.
A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.
On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.
Vorup Petersen, Jacob; Tybirk Nielsen, Jonas; Gunnarsson, Thomas Petursson;
period. Maximal aerobic speed was 0.6 km h(-1) higher (P ...PURPOSE: To investigate the effects of combined strength and speed endurance (SE) training along with a reduced training volume on performance, running economy and muscular adaptations in endurance-trained runners. METHODS: Sixteen male endurance runners (VO2-max: ~60 ml kg(-1) min(-1)) were...... randomly assigned to either a combined strength and SE training (CSS; n = 9) or a control (CON; n = 7) group. For 8 weeks, CSS replaced their normal moderate-intensity training (~63 km week(-1)) with SE (2 × week(-1)) and strength training (2 × week(-1)) as well as aerobic high (1 × week(-1)) and moderate...
Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
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.
Raybourn, Elaine Marie; Mendini, Kip (USA JFKSWCS DOTD, Ft. Bragg, NC); Heneghan, Jerry; Deagle, Edwin (USA JFKSWCS DOTD, Ft. Bragg, NC)
Complex problem solving approaches and novel strategies employed by the military at the squad, team, and commander level are often best learned experimentally. Since live action exercises can be costly, advances in simulation game training technology offer exciting ways to enhance current training. Computer games provide an environment for active, critical learning. Games open up possibilities for simultaneous learning on multiple levels; players may learn from contextual information embedded in the dynamics of the game, the organic process generated by the game, and through the risks, benefits, costs, outcomes, and rewards of alternative strategies that result from decision making. In the present paper we discuss a multiplayer computer game simulation created for the Adaptive Thinking & Leadership (ATL) Program to train Special Forces Team Leaders. The ATL training simulation consists of a scripted single-player and an immersive multiplayer environment for classroom use which leverages immersive computer game technology. We define adaptive thinking as consisting of competencies such as negotiation and consensus building skills, the ability to communicate effectively, analyze ambiguous situations, be self-aware, think innovatively, and critically use effective problem solving skills. Each of these competencies is an essential element of leader development training for the U.S. Army Special Forces. The ATL simulation is used to augment experiential learning in the curriculum for the U.S. Army JFK Special Warfare Center & School (SWCS) course in Adaptive Thinking & Leadership. The school is incorporating the ATL simulation game into two additional training pipelines (PSYOPS and Civil Affairs Qualification Courses) that are also concerned with developing cultural awareness, interpersonal communication adaptability, and rapport-building skills. In the present paper, we discuss the design, development, and deployment of the training simulation, and emphasize how the
Buckthorpe, M; Erskine, R M; Fletcher, G; Folland, J P
This study aimed to delineate the contribution of adaptations in agonist, antagonist, and stabilizer muscle activation to changes in isometric and isoinertial lifting strength after short-term isoinertial resistance training (RT). Following familiarization, 45 men (23.2 ± 2.8 years) performed maximal isometric and isoinertial strength tests of the elbow flexors of their dominant arms before and after 3 weeks of isoinertial RT. During these tasks, surface electromyography (EMG) amplitude was recorded from the agonist (biceps brachii short and long heads), antagonist (triceps brachii lateral head), and stabilizer (anterior deltoid, pectoralis major) muscles and normalized to either Mmax (agonists) or to maximum EMG during relevant reference tasks (antagonist, stabilizers). After training, there was more than a twofold greater increase in training task-specific isoinertial than isometric strength (17% vs 7%). There were also task-specific adaptations in agonist EMG, with greater increases during the isoinertial than isometric strength task [analysis of variance (ANOVA), training × task, P = 0.005]. A novel finding of this study was that training increased stabilizer muscle activation during all the elbow flexion strength tasks (P training effects. RT elicited specific neural adaptations to the training task that appeared to explain the greater increase in isoinertial than isometric strength.
An employee will be qualified to operate a gamma irradiation facility at EMBRARAD after doing a radiation protection training of at least 18 months. After that, the main radiation protection subjects are revised every six months. In that half-yearly training the operators become teachers and so they explain the radiation protection subjects, under the supervision of an instructor. After some years attending the same training, operators do not have motivation to participate in this kind of periodic event due to the same issues covered. Therefore something should be made to revival their interest and motivation to take part in this periodic training. The way chose was adapted a quiz commercial game to revised radiation protection subjects and included it in the periodic training. The game was well accepted by the operators, it caused a competition among them because everybody wanted to win the game and consequently stimulated them to study. (author)
O. F. Opeiko
Full Text Available A synthesis of adaptive PID controller has been executed for flux linkage and speed channels of a vector control system for an induction short-circuited motor. While using an imitation simulation method results of a synthesized system analysis show that the adaptive PID controller has some advantages under conditions of parametric disturbances affecting the object.
Thawar T. Arif
The minimal controller synthesis (MCS) is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.
Shi-Wei Wang; Ding-Li Yu
This paper presents an application of adaptive neural network model-based predictive control (MPC) to the air-fuel ratio of an engine simulation. A multi-layer perceptron (MLP) neural network is trained using two on-line training algorithms: a back propagation algorithm and a recursive least squares (RLS) algorithm. It is used to model parameter uncertainties in the nonlinear dynamics of internal combustion (IC) engines. Based on the adaptive model, an MPC strategy for controlling air-fuel ratio is realized, and its control performance compared with that of a traditional PI controller.A reduced Hessian method, a newly developed sequential quadratic programming (SQP) method for solving nonlinear programming (NLP) problems, is implemented to speed up nonlinear optimization in the MPC.
Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.
George, V. I.; B. Ganesh Kamath; I. Thirunavukkarasu; Ciji Pearl Kurian
The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, are implemented in the real time control. The least mean square algorithm using the adaptive notch fi...
Inamdar, S. R.
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.
Torrence D J Welch
Full Text Available Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations.
Pavlock, Kate Maureen; Less, James L.; Larson, David Nils
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.
WANG Yi-jing; WANG Long
The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.
Hartmann, G. L.; Stein, G.
Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.
Wei, Wei; Wang, Jing; Zuo, Min; Liu, Zaiwen; Du, Junping
In this article, chaos control of satellite attitude motion is considered. Adaptive control based on dynamic compensation is utilised to suppress the chaotic behaviour. Control approaches with three control inputs and with only one control input are proposed. Since the adaptive control employed is based on dynamic compensation, faithful model of the system is of no necessity. Sinusoidal disturbance and parameter uncertainties are considered to evaluate the robustness of the closed-loop system. Both of the approaches are confirmed by theoretical and numerical results.
Clemente-Suárez, Vicente Javier; Fernandes, R J; Arroyo-Toledo, J J; Figueiredo, P; González-Ravé, J M; Vilas-Boas, J P
The objective of the present study was to analyze the autonomic response of trained swimmers to traditional and reverse training periodization models. Seventeen swimmers were divided in two groups, performing a traditional periodization (TPG) or a reverse periodization (RPG) during a period of 10 weeks. Heart rate variability and 50 m swimming performance were analyzed before and after the training programs. After training, the TPG decreased the values of the high frequency band (HF), the number of differences between adjacent normal R-R intervals longer than 50 ms (NN50) and the percentage of differences between adjacent normal R-R intervals more than 50 ms (pNN50), and the RPG increased the values of HF and square root of the mean of the sum of the squared differences between adjacent normal R-R intervals (RMSSD). None of the groups improved significantly their performance in the 50-m test. The autonomic response of swimmers was different depending on the periodization performed, with the reverse periodization model leading to higher autonomic adaption. Complementary, the data suggests that autonomic adaptations were not critical for the 50-m swimming performance. PMID:25804392
Berg, William P; Richards, Brian J; Hannigan, Aaron M; Biller, Kelsey L; Hughes, Michael R
Catching relies on anticipatory and compensatory control processes. Load uncertainty increases anticipatory and compensatory neuromotor effort in catching. This experiment tested the effect of load uncertainty in plyometric catch/throw training on elbow flexion reaction time (RT), movement time (MT) and peak torque, as well as the distribution of anticipatory and compensatory neuromotor effort in catching. We expected load uncertainty training to be superior to traditional training for improving elbow flexion MT and peak torque, as well as for reallocating neuromotor effort from compensatory to anticipatory control in catching. Three groups of men (mean age = 21), load knowledge training (K) (n = 14), load uncertainty training (U) (n = 13) and control (C) (n = 14), participated. Groups K and U trained three times/week for 6 weeks using single-arm catch/throw exercises with 0.45-4.08 kg balls. Sets involved 16 repetitions of four different ball masses presented randomly. Group K had knowledge of ball mass on every repetition, whereas group U never did. Change scores were analyzed using Kruskal-Wallis tests and follow-up Wilcoxon rank-sum tests. Group K improved both RT and MT (by 6.2 and 12 %, respectively), whereas group U did not. Both groups K and U improved peak eccentric elbow flexion torque. Group K reallocated neuromotor effort from compensatory to anticipatory processes in the biceps, triceps and the all muscle average, whereas group U did so in the triceps only. In sum, plyometric catch/throw training caused a reallocation of neuromotor effort from compensatory to anticipatory control in catching. However, load uncertainty training did not amplify this effect and in fact appeared to inhibit the reallocation of neuromotor effort from compensatory to anticipatory control.
Karbach, Julia; Unger, Kerstin
Executive functions (EFs) include a number of higher-level cognitive control abilities, such as cognitive flexibility, inhibition, and working memory, which are instrumental in supporting action control and the flexible adaptation changing environments. These control functions are supported by the prefrontal cortex and therefore develop rapidly across childhood and mature well into late adolescence. Given that executive control is a strong predictor for various life outcomes, such as academic achievement, socioeconomic status, and physical health, numerous training interventions have been designed to improve executive functioning across the lifespan, many of them targeting children and adolescents. Despite the increasing popularity of these trainings, their results are neither robust nor consistent, and the transferability of training-induced performance improvements to untrained tasks seems to be limited. In this review, we provide a selective overview of the developmental literature on process-based cognitive interventions by discussing (1) the concept and the development of EFs and their neural underpinnings, (2) the effects of different types of executive control training in normally developing children and adolescents, (3) individual differences in training-related performance gains as well as (4) the potential of cognitive training interventions for the application in clinical and educational contexts. Based on recent findings, we consider how transfer of process-based executive control trainings may be supported and how interventions may be tailored to the needs of specific age groups or populations. PMID:24847294
GUAN Ping; LIU Xiang-dong; CHEN Jia-bin
The adaptive fuzzy control is applied in the attitude stabilization of flexible satellite. The detailed design procedure of the adaptive fuzzy control system is presented. Two T-S models are used as both controller and identifier. The parameters of the controller could be modified according to the information of the identifier. Simulation results show that the method can effectively cope with the uncertainty of flexible satellite by on-line learning and thus posses the good robustness. With the proposed method, the precise attitude control is accomplished.
National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...
Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza
Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...
Tomelleri, Christopher; Waldner, Andreas; Werner, Cordula; Hesse, Stefan
The main goal of robotic gait rehabilitation is the restoration of independent gait. To achieve this goal different and specific patterns have to be practiced intensively in order to stimulate the learning process of the central nervous system. The gait robot G-EO Systems was designed to allow the repetitive practice of floor walking, stair climbing and stair descending. A novel control strategy allows training in adaptive mode. The force interactions between the foot and the ground were analyzed on 8 healthy volunteers in three different conditions: real floor walking on a treadmill, floor walking on the gait robot in passive mode, floor walking on the gait robot in adaptive mode. The ground reaction forces were measured by a Computer Dyno Graphy (CDG) analysis system. The results show different intensities of the ground reaction force across all of the three conditions. The intensities of force interactions during the adaptive training mode are comparable to the real walking on the treadmill. Slight deviations still occur in regard to the timing pattern of the forces. The adaptive control strategy comes closer to the physiological swing phase than the passive mode and seems to be a promising option for the treatment of gait disorders. Clinical trials will validate the efficacy of this new option in locomotor therapy on the patients.
Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro
The problem of adaptive disturbance attenuation is addressed in this paper using a switching control approach. A finite family of stabilizing controllers is pre-designed, with the assumption that, for any possible operating condition, at least one controller is able to achieve a prescribed level of
LIU Xiao-hua; WANG Xiu-hong; FEN En-min
For a class of continuous-time nonlinear system, a novel robust adaptive fuzzy controller is proposed by using of Lyapunov method. It is proven that the control algorithm is globally stable, the output tracking-error can convergence to a domain of zero under the assumptions. As a result, the system controlled has stronger robustness for disturbance and modeling error.
Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.;
This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...
Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton
The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.
Wang Xin; Li Shaoyuan; Wang Zhongjie
When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
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.
Alexander, J A
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.
Alexander, J A
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. PMID:10110017
The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications.
Full Text Available Problem statement: In order to build an utterance training system for Indonesian language, a speech recognition system designed for Indonesian is necessary. However, the system hardly works well due to the pronunciation variants of non-native utterances may lead to substitution/deletion error. This research investigated the pronunciation variant and proposes acoustic model adaptation to improve performance of the system. Approach: The proposed acoustic model adaptation worked in three steps: to analyze pronunciation variant with knowledge-based and data-derived methods; to align knowledge-based and data-derived results in order to list frequently mispronounced phones with their variants; to perform a state-clustering procedure with the list obtained from the second step. Further, three Speaker Adaptation (SA techniques were used in combination with the acoustic model adaptation and they are compared each other. In order to evaluate and tune the adaptation techniques, perceptual-based evaluation by three human raters is performed to obtain the "true"recognition results. Results: The proposed method achieved an average gain in Hit + Rejection (the percentage of correctly accepted and correctly rejected utterances by the system as the human raters do of 2.9 points and 2 points for native and non-native subjects, respectively, when compared with the system without adaptation. Average gains of 12.7 and 6.2 points for native and non-native students in Hit + Rejection were obtained by combining SA to the acoustic model adaptation. Conclusion/Recommendations: Performance evaluation of the adapted system demonstrated that the proposed acoustic model adaptation can improve Hit even though there is a slight increase of False Alarm (FA, the percentage of incorrectly accepted utterances by the system of which the human raters reject. The performance of the proposed acoustic model adaptation depends strongly on the effectiveness of state-clustering procedure
Jastrzębska, Maria; Kaczmarczyk, Mariusz; Jastrzębski, Zbigniew
Jastrzębska, M, Kaczmarczyk, M, and Jastrzębski, Z. Effect of vitamin D supplementation on training adaptation in well-trained soccer players. J Strength Cond Res 30(9): 2648-2655, 2016-There is growing body of evidence implying that vitamin D may be associated with athletic performance, however, studies examining the effects of vitamin D on athletic performance are inconsistent. Moreover, very little literature exists about the vitamin D and training efficiency or adaptation, especially in high-level, well-trained athletes. The purpose of the current study was to investigate the effect of vitamin D supplementation on training adaptation in well-trained football players. The subjects were divided into 2 groups: the placebo group (PG) and the experimental group (SG, supplemented with vitamin D, 5,000 IU per day). Both groups were subjected to High Intensity Interval Training Program. The selection to the groups was based on peak power results attained before the experiment and position on the field. Blood samples for vitamin D level were taken from the players. In addition, total work, 5, 10, 20, and 30 m running speed, squat jump, and countermovement jump height were determined. There were no significant differences between SG and PG groups for any power-related characteristics at baseline. All power-related variables, except the 30 m sprint running time, improved significantly in response to interval training. However, the mean change scores (the differences between posttraining and pretraining values) did not differ significantly between SG and PG groups. In conclusion, an 8-week vitamin D supplementation in highly trained football players was not beneficial in terms of response to High Intensity Interval Training. Given the current level of evidence, the recommendation to use vitamin D supplements in all athletes to improve performance or training gains would be premature. To avoid a seasonal decrease in 25(OH)D level or to obtain optimal vitamin D levels, the
Dudley, Gary A.; Miller, Bruce J.; Buchanan, Paul; Tesch, Per A.
The importance of eccentric (ecc) muscle actions in resistance training for the maintenance of muscle strength and mass in hypogravity was investigated in experiments in which human subjects, divided into three groups, were asked to perform four-five sets of 6 to 12 repetitions (rep) per set of three leg press and leg extension exercises, 2 days each weeks for 19 weeks. One group, labeled 'con', performed each rep with only concentric (con) actions, while group con/ecc with performed each rep with only ecc actions; the third group, con/con, performed twice as many sets with only con actions. Control subjects did not train. It was found that resistance training wih both con and ecc actions induced greater increases in muscle strength than did training with only con actions.
McDermott, William J; Van Emmerik, Richard E A; Hamill, Joseph
It has been suggested that stronger coupling between locomotory and breathing rhythms may occur as a result of training in the particular movement pattern and also may reduce the perceived workload or metabolic cost of the movement. Research findings on human locomotor-respiratory coordination are equivocal, due in part to the fact that assessment techniques range in sensitivity to important aspects of coordination (e.g. temporal ordering of patterns, half-integer couplings and changes in frequency and phase coupling). An additional aspect that has not received much attention is the adaptability of this coordination to changes in task constraints. The current study investigated the effect of running training on the locomotor-respiratory coordination and the adaptive strategies observed across a wide range of walking and running speeds. Locomotor-respiratory coordination was evaluated by the strength and variability of both frequency and phase coupling patterns that subjects displayed within and across the speed conditions. Male subjects (five runners, five non-runners) locomoted at seven different treadmill speeds. Group results indicated no differences between runners and non-runners with respect to breathing parameters, stride parameters, as well as the strength and variability of the coupling at each speed. Individual results, however, showed that grouping subjects masks large individual differences and strategies across speeds. Coupling strategies indicated that runners show more stable dominant couplings across locomotory speeds than non-runners do. These findings suggest that running training does not change the strength of locomotor-respiratory coupling but rather how these systems adapt to changing speeds.
Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato
This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.
Full Text Available Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.
Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...
Butler, H.; Honderd, G.; Amerongen, van, W.E.
This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...
Full Text Available The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, are implemented in the real time control. The least mean square algorithm using the adaptive notch filter is applied to the flexible spacecraft. This study will show that the adaptive vibration controller successfully stabilizes the uncertain and it will accurately control the vibration of flexible spacecraft. The Least mean square algorithm is applied in flexible spacecraft to attenuate the vibration. The simulation studies are carried out in a Matlab/Simulink environment.
Krustrup, Peter; Christensen, Jesper F.; Randers, Morten Bredsgaard;
We examined the physical demands of small-sided soccer games in untrained middle-age males and muscle adaptations and performance effects over 12 weeks of recreational soccer training in comparison with continuous running. Thirty-eight healthy subjects (20-43 years) were randomized into a soccer...... (SO), running (RU) and control (CO) group. Two-three weekly 1-h training sessions were performed. Muscle lactate (30.1 +/- 4.1 vs. 15.6 +/- 3.3 mmol/kg d.w.), blood lactate, blood glucose and time above 90% HR(max) (20 +/- 4% vs. 1 +/- 1%) were higher (p training in SO than in RU. After...... 12 weeks of training, quadriceps muscle mass and mean muscle fibre area were 9 and 15% larger (p
Udink ten Cate, A.J.
The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there
Merry, Troy L; Ristow, Michael
A popular belief is that reactive oxygen species (ROS) and reactive nitrogen species (RNS) produced during exercise by the mitochondria and other subcellular compartments ubiquitously cause skeletal muscle damage, fatigue and impair recovery. However, the importance of ROS and RNS as signals in the cellular adaptation process to stress is now evident. In an effort to combat the perceived deleterious effects of ROS and RNS it has become common practice for active individuals to ingest supplements with antioxidant properties, but interfering with ROS/RNS signalling in skeletal muscle during acute exercise may blunt favourable adaptation. There is building evidence that antioxidant supplementation can attenuate endurance training-induced and ROS/RNS-mediated enhancements in antioxidant capacity, mitochondrial biogenesis, cellular defence mechanisms and insulin sensitivity. However, this is not a universal finding, potentially indicating that there is redundancy in the mechanisms controlling skeletal muscle adaptation to exercise, meaning that in some circumstances the negative impact of antioxidants on acute exercise response can be overcome by training. Antioxidant supplementation has been more consistently reported to have deleterious effects on the response to overload stress and high-intensity training, suggesting that remodelling of skeletal muscle following resistance and high-intensity exercise is more dependent on ROS/RNS signalling. Importantly there is no convincing evidence to suggest that antioxidant supplementation enhances exercise-training adaptions. Overall, ROS/RNS are likely to exhibit a non-linear (hormetic) pattern on exercise adaptations, where physiological doses are beneficial and high exposure (which would seldom be achieved during normal exercise training) may be detrimental.
Full Text Available The obesity epidemic continues rising as a global health challenge, despite the increasing public awareness and the use of lifestyle and medical interventions. The biomedical community is urged to develop new treatments to obesity. Excess energy is stored as fat in white adipose tissue (WAT, dysfunction of which lie at the core of obesity and associated metabolic disorders. In contrast, brown adipose tissue (BAT burns fat and dissipates chemical energy as heat. The development and activation of brown-like adipocytes, also known as beige cells, result in WAT browning and thermogenesis. The recent discovery of brown and beige adipocytes in adult humans has sparked the exploration of the development, regulation, and function of these thermogenic adipocytes. The central nervous system (CNS drives the sympathetic nerve activity in BAT and WAT to control heat production and energy homeostasis. This review provides an overview of the integration of thermal, hormonal, and nutritional information on hypothalamic circuits in thermoregulation.
The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.
This program management guide describes the proper implementation standard for core training as outlined in the DOE Radiological Control (RadCon) Manual. The guide is to assist those individuals, both within the Department of Energy (DOE) and Managing and Operating (M and O) contractors, identified as having responsibility for implementing the core training recommended by the RadCon Manual. The management guide is divided into the following sections: introduction; instructional materials development; training program standards and policies; and course-specific information. The goal of the core training program is to provide a standardized, baseline knowledge for those individuals completing the core training. Standardization of the knowledge provides personnel with the information necessary to perform their assigned duties at a predetermined level of expertise. Implementing a core training program ensures consistent and appropriate training of personnel
Venditti, P; Napolitano, G; Barone, D; Di Meo, S
Aim of the present study was to test, by vitamin E treatment, the hypothesis that muscle adaptive responses to training are mediated by free radicals produced during the single exercise sessions. Therefore, we determined aerobic capacity of tissue homogenates and mitochondrial fractions, tissue content of mitochondrial proteins and expression of factors (PGC-1, NRF-1, and NRF-2) involved in mitochondrial biogenesis. Moreover, we determined the oxidative damage extent, antioxidant enzyme activities, and glutathione content in both tissue preparations, mitochondrial ROS production rate. Finally we tested mitochondrial ROS production rate and muscle susceptibility to oxidative stress. The metabolic adaptations to training, consisting in increased muscle oxidative capacity coupled with the proliferation of a mitochondrial population with decreased oxidative capacity, were generally prevented by antioxidant supplementation. Accordingly, the expression of the factors involved in mitochondrial biogenesis, which were increased by training, was restored to the control level by the antioxidant treatment. Even the training-induced increase in antioxidant enzyme activities, glutathione level and tissue capacity to oppose to an oxidative attach were prevented by vitamin E treatment. Our results support the idea that the stimulus for training-induced adaptive responses derives from the increased production, during the training sessions, of reactive oxygen species that stimulates the expression of PGC-1, which is involved in mitochondrial biogenesis and antioxidant enzymes expression. On the other hand, the observation that changes induced by training in some parameters are only attenuated by vitamin E treatment suggests that other signaling pathways, which are activated during exercise and impinge on PGC-1, can modify the response to the antioxidant integration.
Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro
Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.
Henriksson, J; Svedenhag, J; Richter, Erik;
The main purpose of the present study was to test the hypothesis that adrenergic stimulation of muscle fibres during exercise is a major stimulus for the training-induced enhancement of skeletal muscle respiratory capacity. Therefore, Sprague-Dawley rats either underwent bilateral surgical ablation...... of the adrenal medulla or were sham-operated. Furthermore, unilateral surgical extirpation of the lumbar sympathetic chain was performed. Half of the rats were then trained for 12 weeks by swimming (up to 5.5 h X day-1, 4 days X week-1) and the remaining rats were sedentary controls. In the gastrocnemius muscle......-induced enzyme adaptation after adrenodemedullation and/or sympathectomy was not significantly lower than these control values. In sham-operated rats, training decreased resting plasma insulin and glucagon levels and increased liver glycogen content. Similar changes were induced by adrenodemedullation...
H.S. Tzou; Bao, Y
Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...
Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.
Frederico D Lima
Full Text Available BACKGROUND AND AIMS: Although acute exhaustive exercise is known to increase liver reactive oxygen species (ROS production and aerobic training has shown to improve the antioxidant status in the liver, little is known about mitochondria adaptations to aerobic training. The main objective of this study was to investigate the effects of the aerobic training on oxidative stress markers and antioxidant defense in liver mitochondria both after training and in response to three repeated exhaustive swimming bouts. METHODS: Wistar rats were divided into training (n = 14 and control (n = 14 groups. Training group performed a 6-week swimming training protocol. Subsets of training (n = 7 and control (n = 7 rats performed 3 repeated exhaustive swimming bouts with 72 h rest in between. Oxidative stress biomarkers, antioxidant activity, and mitochondria functionality were assessed. RESULTS: Trained group showed increased reduced glutathione (GSH content and reduced/oxidized (GSH/GSSG ratio, higher superoxide dismutase (MnSOD activity, and decreased lipid peroxidation in liver mitochondria. Aerobic training protected against exhaustive swimming ROS production herein characterized by decreased oxidative stress markers, higher antioxidant defenses, and increases in methyl-tetrazolium reduction and membrane potential. Trained group also presented higher time to exhaustion compared to control group. CONCLUSIONS: Swimming training induced positive adaptations in liver mitochondria of rats. Increased antioxidant defense after training coped well with exercise-produced ROS and liver mitochondria were less affected by exhaustive exercise. Therefore, liver mitochondria also adapt to exercise-induced ROS and may play an important role in exercise performance.
Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A
Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.
Wamsley, Mary Ann, Ed.; Vermeire, Donna M., Ed.
This Cooperative Extension Service publication from Mississippi State University is a training guide for commercial applicators. Weed control, vertebrate pest control, and environmental considerations and restrictions are the three major parts of the document. The weed control section discusses non-pesticide, mechanical, and biological control as…
Lemos, João M; Igreja, José M
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts
Full Text Available Cerebral Palsy (CP results from an insult to the developing brain and is associated with deficits in locomotor and manual skills and in sensorimotor adaptation. We hypothesized that the poor sensorimotor adaptation in persons with CP is related to their high execution variability and does not reflect a general impairment in adaptation learning. We studied the interaction between performance variability and adaptation deficits using a multi-session locomotor adaptation design in persons with CP. Six adolescents with diplegic CP were exposed, during a period of 15 weeks, to a repeated split-belt treadmill perturbation spread over 30 sessions and were tested again 6 months after the end of training. Compared to age-matched healthy controls, subjects with CP showed poor adaptation and high execution variability in the first exposure to the perturbation. Following training they showed marked reduction in execution variability and an increase in learning rates. The reduction in variability and the improvement in adaptation were highly correlated in the CP group and were retained 6 months after training. Interestingly, despite reducing their variability in the washout phase, subjects with CP did not improve learning rates during washout phases that were introduced only 4 times during the experiment. Our results suggest that locomotor adaptation in subjects with CP is related to their execution variability. Nevertheless, while variability reduction is generalized to other locomotor contexts, the development of savings requires both reduction in execution variability and multiple exposures to the perturbation.
Bray, Steven R; Graham, Jeffrey D; Saville, Paul D
The purpose of the study was to investigate the effects of two weeks of self-control strength training on maximum cardiovascular exercise performance. Forty-one participants completed a cognitive self-control depletion task (Stroop task) followed by a maximal graded cycling test and were randomized to training (maximal endurance contractions of spring handgrip trainers, twice daily) or no-treatment control groups. At follow-up (2 weeks), half of each group completed either a time-matched or trial-matched Stroop task followed by another maximal graded cycling test. Results showed a significant 2-way (training X time) interaction (P cognitive task) interaction (P = 0.07). Decomposition of the interactions revealed that across sessions cycling performance increased in both training groups, did not change in the trial-matched cognitive task control group, and declined in the time-matched control group. We conclude that isometric handgrip training leads to self-control strength adaptations that enhance maximal cardiovascular exercise performance or tolerance of exercise at maximal levels of effort. PMID:25278342
Oudejans, Raoul R. D.; Heubers, Sjoerd; Ruitenbeek, Jean-Rene J. A. C.; Janssen, Thomas W. J.
We examined the effects of visual control training on expert wheelchair basketball shooting, a skill more difficult than in regular basketball, as players shoot from a seated position to the same rim height. The training consisted of shooting with a visual constraint that forced participants to use target information as late as possible.…
Thor I. Fossen
Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.
Full Text Available Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive control scheme that involves manipulating a controller of a general type to improve its performance as measured by an evaluation function. The developed method is closely related to a theory of Reinforcement Learning (RL but imposes a practical assumption made for faster learning. We assume that a value function of RL can be approximated by a function of Euclidean distance from a goal state and an action executed at the state. And, we propose to use it for the gradient search as an evaluation function. Simulation results provided through application of the proposed scheme to a pole-balancing problem using a linear state feedback controller and fuzzy controller verify the scheme’s efficacy.
Akira Inoue; Ming-Cong Deng
This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.
Fernanda R. Roque
Full Text Available OBJECTIVES: Aerobic exercise training prevents cardiovascular risks. Regular exercise promotes functional and structural adaptations that are associated with several cardiovascular benefits. The aim of this study is to investigate the effects of swimming training on coronary blood flow, adenosine production and cardiac capillaries in normotensive rats. METHODS: Wistar rats were randomly divided into two groups: control (C and trained (T. An exercise protocol was performed for 10 weeks and 60 min/day with a tail overload of 5% bodyweight. Coronary blood flow was quantified with a color microsphere technique, and cardiac capillaries were quantified using light microscopy. Adenine nucleotide hydrolysis was evaluated by enzymatic activity, and protein expression was evaluated by western blot. The results are presented as the means ± SEMs (p<0.05. RESULTS: Exercise training increased the coronary blood flow and the myocardial capillary-to-fiber ratio. Moreover, the circulating and cardiac extracellular adenine nucleotide hydrolysis was higher in the trained rats than in the sedentary rats due to the increased activity and protein expression of enzymes, such as E-NTPDase and 59- nucleotidase. CONCLUSIONS: Swimming training increases coronary blood flow, number of cardiac capillaries, and adenine nucleotide hydrolysis. Increased adenosine production may be an important contributor to the enhanced coronary blood flow and angiogenesis that were observed in the exercise-trained rats; collectively, these results suggest improved myocardial perfusion.
... 49 Transportation 4 2010-10-01 2010-10-01 false Locomotive of each train operating in train stop... OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Automatic Train Stop, Train Control and Cab Signal Systems Rules and Instructions; Locomotives § 236.566 Locomotive of each train operating...
Ramirez-Sarmiento, Alba; Orozco-Levi, Mauricio; Guell, Rosa; Barreiro, Esther; Hernandez, Nuria; Mota, Susana; Sangenis, Merce; Broquetas, Joan M; Casan, Pere; Gea, Joaquim
The present study was aimed at evaluating the effects of a specific inspiratory muscle training protocol on the structure of inspiratory muscles in patients with chronic obstructive pulmonary disease. Fourteen patients (males, FEV1, 24 +/- 7% predicted) were randomized to either inspiratory muscle or sham training groups. Supervised breathing using a threshold inspiratory device was performed 30 minutes per day, five times a week, for 5 consecutive weeks. The inspiratory training group was subjected to inspiratory loading equivalent to 40 to 50% of their maximal inspiratory pressure. Biopsies from external intercostal muscles and vastus lateralis (control muscle) were taken before and after the training period. Muscle samples were processed for morphometric analyses using monoclonal antibodies against myosin heavy chain isoforms I and II. Increases in both the strength and endurance of the inspiratory muscles were observed in the inspiratory training group. This improvement was associated with increases in the proportion of type I fibers (by approximately 38%, p < 0.05) and in the size of type II fibers (by approximately 21%, p < 0.05) in the external intercostal muscles. No changes were observed in the control muscle. The study demonstrates that inspiratory training induces a specific functional improvement of the inspiratory muscles and adaptive changes in the structure of external intercostal muscles. PMID:12406842
National Aeronautics and Space Administration — MYMIC will analyze, design, develop and evaluate the Virtual Control Room Compressor Station (VCoR-CS) training system. VCoR-CS will provide procedural...
For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.
Jing Tang; Zhihui Huang; Yan Tan; Nina Zhang; Anping Tan; Jun Chen; Jianfeng Chen
Biofeedback therapy is a well-known and effective therapeutic treatment for constipation. A previous study suggested that adaptive biofeedback (ABF) training was more effective than traditional (fixed training parameters) biofeedback training. The aim of this study was to verify the effectiveness of ABF in relieving constipation-related symptoms. We noticed that in traditional biofeedback training, a patient usually receives the training twice per week. The long training sessions usually led ...
Wen, John Ting-Yung; Balas, Mark J.
Paper discusses generalization of scheme for adaptive control of finite-dimensional system to infinite-dimensional Hilbert space. Approach involves generalization of command-generator tracker (CGT) theory. Does not require reference model to be same order as that of plant, and knowledge of order of plant not needed. Suitable for application to high-order systems, main emphasis on adjustment of low-order feedback-gain matrix. Analysis particularly relevant to control of large, flexible structures.
Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique
This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.
Mississippi State Univ., State College. Cooperative Extension Service.
This Cooperative Extension Service publication from Mississippi State University is a training guide for commercial pesticide applicators. Focusing on ornamental and turf plant pest control, this publication examines the control of plant diseases, insects, and weeds. The contents are divided into a section on ornamental pest control and one on…
Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features ...
Full Text Available Abstract Background To determine the impact of AA supplementation during resistance training on body composition, training adaptations, and markers of muscle hypertrophy in resistance-trained males. Methods In a randomized and double blind manner, 31 resistance-trained male subjects (22.1 ± 5.0 years, 180 ± 0.1 cm, 86.1 ± 13.0 kg, 18.1 ± 6.4% body fat ingested either a placebo (PLA: 1 g·day-1 corn oil, n = 16 or AA (AA: 1 g·day-1 AA, n = 15 while participating in a standardized 4 day·week-1 resistance training regimen. Fasting blood samples, body composition, bench press one-repetition maximum (1RM, leg press 1RM and Wingate anaerobic capacity sprint tests were completed after 0, 25, and 50 days of supplementation. Percutaneous muscle biopsies were taken from the vastus lateralis on days 0 and 50. Results Wingate relative peak power was significantly greater after 50 days of supplementation while the inflammatory cytokine IL-6 was significantly lower after 25 days of supplementation in the AA group. PGE2 levels tended to be greater in the AA group. However, no statistically significant differences were observed between groups in body composition, strength, anabolic and catabolic hormones, or markers of muscle hypertrophy (i.e. total protein content or MHC type I, IIa, and IIx protein content and other intramuscular markers (i.e. FP and EP3 receptor density or MHC type I, IIa, and IIx mRNA expression. Conclusion AA supplementation during resistance-training may enhance anaerobic capacity and lessen the inflammatory response to training. However, AA supplementation did not promote statistically greater gains in strength, muscle mass, or influence markers of muscle hypertrophy.
Full Text Available Few studies have addressed action control training. In the current study, participants were trained over 19 days in an adaptive training task that demanded constant switching, maintenance and updating of novel action rules. Participants completed an executive functions battery before and after training that estimated processing speed, working memory updating, set-shifting, response inhibition and fluid intelligence. Participants in the training group showed greater improvement than a no-contact control group in processing speed, indicated by reduced reaction times in speeded classification tasks. No other systematic group differences were found across the different pre-post measurements. Ex-Gaussian fitting of the reaction-time distribution revealed that the reaction time reduction observed among trained participants was restricted to the right tail of the distribution, previously shown to be related to working memory. Furthermore, training effects were only found in classification tasks that required participants to maintain novel stimulus-response rules in mind, supporting the notion that the training improved working memory abilities. Training benefits were maintained in a 10-month follow-up, indicating relatively long-lasting effects. The authors conclude that training improved action-related working memory abilities.
Food irradiation can offer its full potential benefit only if irradiation facilities and processes are subject to strict control measures. The training of personnel involved in the process and inspection or control of the process and facilities must form an integral part of all food irradiation control procedures. Thus, training courses for irradiator operators, plant managers and supervisors that address proper processing with emphasis on good manufacturing practices (GMPs), dosimetry, record keeping and lot identification should be organized. For food control officials, training in the appropriate inspection procedures required for food irradiation facilities and processes is essential. Last but not least, voluntary compliance is deemed as an ideal but conceivable strategy to sustain and acceptable degree of quality assurance and facilitate effective control and hence should be promoted. (author). 13 refs
This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems : Duffing oscillator and Rǒssler chaos.
This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems: Duffing oscillator and Rossler chaos.
Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.
To guarantee the real-time transmission of a video stream,based on the stochastic optimal control method,a frame layer adaptive rate control algorithm for the wireless transcoder is proposed,which is capable of dynamically determining the transcoder's objective bit rate,according to the bandwidth variation of the wireless channel and the bufier occupancy. Then the transient performance,steady performance,and computational complexity of the algorithm are analyzed.Finally,the experiment results demonstrate that the algorithm can improve the synthetic performance of rate control through the compromise between the end-to-end delay and the playout quality.
Larsen, Kim Guldstrand; Mikučionis, Marius; Taankvist, Jakob Haahr
In a series of contributions Olderog et al. have formulated and verified safety controllers for a number of lane-maneuvers on multilane roads. Their work is characterized by great clarity and elegance partly due to the introduction of a special-purpose Multi-Lane Spatial Logic. In this paper, we...... want to illustrate the potential of current modelchecking technology for automatic synthesis of optimal yet safe (collision-free) controllers. We demonstrate this potential on an Adaptive Cruise Control problem, being a small part of the overall safety problem considered by Olderog....
It is important to develop control techniques able to control not only known chaos but also chaotic systems with unknown parameters. This paper proposes a novel adaptive tracking control approach for identifying the unknown parameters and controlling the chaos, which is not closely related to the particular chaotic system to be controlled. The global uniform boundedness of estimated parameters and the asymptotical stability of the tracking errors are proved by Lyapunov stability theory and LaSalle-Yoshizawa theorem. The suggested method enables stabilization of chaotic motion to a steady state ad well as tracking of any desired trajectory to be achieved in a systematic way. Computer simulation on a complex chaotic system illustrtes the effectiveness of the proposed control method.
As the Department of Energy (DOE) works to standardize the training for individuals performing materials control and accountability (MC and A) functions, the need for a definition of the appropriate training for MC and A auditors has become apparent. In order to meet the DOE requirement for individual training plans for all staff performing MC and A functions, the following set of guidelines was developed for consideration as applicable to MC and A auditors. The application of these guidelines to specific operating environments at individual DOE sites may require modification to some of the tables. The paper presents one method of developing individual training programs for an MC and A auditor or for an MC and A audit group based on the requirements for internal audits and assessments included in DOE Order 5633.3, Control and Accountability for Nuclear Materials
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Parker, Robert C., Comp.
This Cooperative Extension Service publication from Mississippi State University is a training guide for commercial pesticide applicators. Focusing on forest pest control, this publication examines plant and animal pest control practices for southern tree species. Contents include: (1) identification of insects, diseases, and weed tree species;…
Mississippi State Univ., State College. Cooperative Extension Service.
This Cooperative Extension Service publication from Mississippi State University is a training guide for commercial pesticide applicators. Focusing on agricultural pest control, this publication includes a full range of topics from uses of pesticides for agricultural animal pest control to the toxicity of common pesticides to fish and bees.…
Jie LUO; Chengyu CAO
This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.
Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy
The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems.
Full Text Available In this study, vertical rail vehicle vibrations are controlled by the use of conventional PID and parameters which are adaptive to PID controllers. A parameters adaptive PID controller is designed to improve the passenger comfort by intuitional usage of this method that renews the parameters online and sensitively under variable track inputs. Sinusoidal vertical rail misalignment and measured real rail irregularity are considered as two different disruptive effects of the system. Active vibration control is applied to the system through the secondary suspension. The active suspension application of rail vehicle is examined by using 5-DOF quarter-rail vehicle model by using Manchester benchmark dynamic parameters. The new parameters of adaptive controller are optimized by means of genetic algorithm toolbox of MATLAB. Simulations are performed at maximum urban transportation speed (90 km/h of the rail vehicle with ±5% load changes of rail vehicle body to test the robustness of controllers. As a result, superior performance of parameters of adaptive controller is determined in time and frequency domain.
Neuper, Christa; Pfurtscheller, Gert
Brain-computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see ). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Electroencephalogram (EEG)). Sophisticated pattern recognition and classification algorithms convert neural activity into the required control signals. BCI research has focused heavily on developing powerful signal processing and machine learning techniques to accurately classify neural activity [2-4].
Full Text Available Problem statement: Research into robot motion control offers research opportunities that will change scientists and engineers for year to come. Autonomous robots are increasingly evident in many aspects of industry and everyday life and a robust robot motion control can be used for homeland security and many consumer applications. This study discussed the adaptive fuzzy knowledge based controller for robot motion control in indoor and outdoor environment. Approach: The proposed method consisted of two components: the process monitor that detects changes in the process characteristics and the adaptation mechanism that used information passed to it by the process monitor to update the controller parameters. Results: Experimental evaluation had been done in both indoor and outdoor environment where the robot communicates with the base station through its Wireless fidelity antenna and the performance monitor used a set of five performance criteria to access the fuzzy knowledge based controller. Conclusion: The proposed method had been found to be robust.
Montani, Veronica; De Filippo De Grazia, Michele; Zorzi, Marco
A growing body of evidence suggests that action videogames could enhance a variety of cognitive skills and more specifically attention skills. The aim of this study was to develop a novel adaptive videogame to support the rehabilitation of the most common consequences of traumatic brain injury (TBI), that is the impairment of attention and executive functions. TBI patients can be affected by psychomotor slowness and by difficulties in dealing with distraction, maintain a cognitive set for a long time, processing different simultaneously presented stimuli, and planning purposeful behavior. Accordingly, we designed a videogame that was specifically conceived to activate those functions. Playing involves visuospatial planning and selective attention, active maintenance of the cognitive set representing the goal, and error monitoring. Moreover, different game trials require to alternate between two tasks (i.e., task switching) or to perform the two tasks simultaneously (i.e., divided attention/dual-tasking). The videogame is controlled by a multidimensional adaptive algorithm that calibrates task difficulty on-line based on a model of user performance that is updated on a trial-by-trial basis. We report simulations of user performance designed to test the adaptive game as well as a validation study with healthy participants engaged in a training protocol. The results confirmed the involvement of the cognitive abilities that the game is supposed to enhance and suggested that training improved attentional control during play.
Full Text Available A growing body of evidence suggests that action videogames could enhance a variety of cognitive skills and more specifically attention skills. The aim of this study was to develop a novel adaptive videogame to support the rehabilitation of the most common consequences of traumatic brain injury (TBI, that is the impairment of attention and executive functions. TBI patients can be affected by psychomotor slowness and by difficulties in dealing with distraction, maintain a cognitive set for a long time, processing different simultaneously presented stimuli, and planning purposeful behaviour. Accordingly, we designed a videogame that was specifically conceived to activate those functions. Playing involves visuospatial planning and selective attention, active maintenance of the cognitive set representing the goal, and error monitoring. Moreover, different game trials require to alternate between two tasks (i.e., task switching or to perform the two tasks simultaneously (i.e., divided attention / dual-tasking. The videogame is controlled by a multidimensional adaptive algorithm that calibrates task difficulty on-line based on a model of user performance that is updated on a trial-by-trial basis. We report simulations of user performance designed to test the adaptive game as well as a validation study with healthy participants engaged in a training protocol. The results confirmed the involvement of the cognitive abilities that the game is supposed to enhance and suggested that training improved attentional control during play.
Burgomaster, Kirsten A; Howarth, Krista R; Phillips, Stuart M; Rakobowchuk, Mark; Macdonald, Maureen J; McGee, Sean L; Gibala, Martin J
Low-volume 'sprint' interval training (SIT) stimulates rapid improvements in muscle oxidative capacity that are comparable to levels reached following traditional endurance training (ET) but no study has examined metabolic adaptations during exercise after these different training strategies. We hypothesized that SIT and ET would induce similar adaptations in markers of skeletal muscle carbohydrate (CHO) and lipid metabolism and metabolic control during exercise despite large differences in training volume and time commitment. Active but untrained subjects (23 +/- 1 years) performed a constant-load cycling challenge (1 h at 65% of peak oxygen uptake (.VO(2peak)) before and after 6 weeks of either SIT or ET (n = 5 men and 5 women per group). SIT consisted of four to six repeats of a 30 s 'all out' Wingate Test (mean power output approximately 500 W) with 4.5 min recovery between repeats, 3 days per week. ET consisted of 40-60 min of continuous cycling at a workload that elicited approximately 65% (mean power output approximately 150 W) per day, 5 days per week. Weekly time commitment (approximately 1.5 versus approximately 4.5 h) and total training volume (approximately 225 versus approximately 2250 kJ week(-1)) were substantially lower in SIT versus ET. Despite these differences, both protocols induced similar increases (P < 0.05) in mitochondrial markers for skeletal muscle CHO (pyruvate dehydrogenase E1alpha protein content) and lipid oxidation (3-hydroxyacyl CoA dehydrogenase maximal activity) and protein content of peroxisome proliferator-activated receptor-gamma coactivator-1alpha. Glycogen and phosphocreatine utilization during exercise were reduced after training, and calculated rates of whole-body CHO and lipid oxidation were decreased and increased, respectively, with no differences between groups (all main effects, P < 0.05). Given the markedly lower training volume in the SIT group, these data suggest that high-intensity interval training is a time
Burgomaster, Kirsten A; Howarth, Krista R; Phillips, Stuart M; Rakobowchuk, Mark; MacDonald, Maureen J; McGee, Sean L; Gibala, Martin J
Low-volume ‘sprint’ interval training (SIT) stimulates rapid improvements in muscle oxidative capacity that are comparable to levels reached following traditional endurance training (ET) but no study has examined metabolic adaptations during exercise after these different training strategies. We hypothesized that SIT and ET would induce similar adaptations in markers of skeletal muscle carbohydrate (CHO) and lipid metabolism and metabolic control during exercise despite large differences in training volume and time commitment. Active but untrained subjects (23 ± 1 years) performed a constant-load cycling challenge (1 h at 65% of peak oxygen uptake before and after 6 weeks of either SIT or ET (n = 5 men and 5 women per group). SIT consisted of four to six repeats of a 30 s ‘all out’ Wingate Test (mean power output ∼500 W) with 4.5 min recovery between repeats, 3 days per week. ET consisted of 40–60 min of continuous cycling at a workload that elicited ∼65% (mean power output ∼150 W) per day, 5 days per week. Weekly time commitment (∼1.5 versus∼4.5 h) and total training volume (∼225 versus∼2250 kJ week−1) were substantially lower in SIT versus ET. Despite these differences, both protocols induced similar increases (P < 0.05) in mitochondrial markers for skeletal muscle CHO (pyruvate dehydrogenase E1α protein content) and lipid oxidation (3-hydroxyacyl CoA dehydrogenase maximal activity) and protein content of peroxisome proliferator-activated receptor-γ coactivator-1α. Glycogen and phosphocreatine utilization during exercise were reduced after training, and calculated rates of whole-body CHO and lipid oxidation were decreased and increased, respectively, with no differences between groups (all main effects, P < 0.05). Given the markedly lower training volume in the SIT group, these data suggest that high-intensity interval training is a time-efficient strategy to increase skeletal muscle oxidative capacity and induce specific metabolic
Zanesco, Anthony P; King, Brandon G; Maclean, Katherine A; Saron, Clifford D
Various forms of mental training have been shown to improve performance on cognitively demanding tasks. Individuals trained in meditative practices, for example, show generalized improvements on a variety of tasks assessing attentional performance. A central claim of this training, derived from contemplative traditions, posits that improved attentional performance is accompanied by subjective increases in the stability and clarity of concentrative engagement with one's object of focus, as well as reductions in felt cognitive effort as expertise develops. However, despite frequent claims of mental stability following training, the phenomenological correlates of meditation-related attentional improvements have yet to be characterized. In a longitudinal study, we assessed changes in executive control (performance on a 32-min response inhibition task) and retrospective reports of task engagement (concentration, motivation, and effort) following one month of intensive, daily Vipassana meditation training. Compared to matched controls, training participants exhibited improvements in response inhibition accuracy and reductions in reaction time variability. The training group also reported increases in concentration, but not effort or motivation, during task performance. Critically, increases in concentration predicted improvements in reaction time variability, suggesting a link between the experience of concentrative engagement and ongoing fluctuations in attentional stability. By incorporating experiential measures of task performance, the present study corroborates phenomenological accounts of stable, clear attentional engagement with the object of meditative focus following extensive training. These results provide initial evidence that meditation-related changes in felt experience accompany improvements in adaptive, goal-directed behavior, and that such shifts may reflect accurate awareness of measurable changes in performance.
Anthony Paul Zanesco
Full Text Available Various forms of mental training have been shown to improve performance on cognitively demanding tasks. Individuals trained in meditative practices, for example, show generalized improvements on a variety of tasks assessing attentional performance. A central claim of this training, derived from contemplative traditions, posits that improved attentional performance is accompanied by subjective increases in the stability and clarity of concentrative engagement with one’s object of focus, as well as reductions in felt cognitive effort as expertise develops. However, despite frequent claims of mental stability following training, the phenomenological correlates of meditation-related attentional improvements have yet to be characterized. In a longitudinal study, we assessed changes in executive control (performance on a 32-minute response inhibition task and retrospective reports of task engagement (concentration, motivation, and effort following one month of intensive, daily Vipassana meditation training. Compared to matched controls, training participants exhibited improvements in response inhibition accuracy and reductions in reaction time variability. The training group also reported increases in concentration, but not effort or motivation, during task performance. Critically, increases in concentration predicted improvements in reaction time variability, suggesting a link between the experience of concentrative engagement and ongoing fluctuations in attentional stability. By incorporating experiential measures of task performance, the present study corroborates phenomenological accounts of stable, clear attentional engagement with the object of meditative focus following extensive training. These results provide initial evidence that meditation-related changes in felt experience accompany improvements in adaptive, goal-directed behavior, and that such shifts may reflect accurate awareness of measurable changes in performance.
Various types of intensive training courses to suit radiation workers in different fields were sponsored by both the Atomic Energy Council of Executive Yuan and the National Health Administration of Executive Yuan, Republic of China during the past seven years. During the years 1974-79, the number of radiation workers attending each training course, their age, sex and educational background are presented in detail. The typical course contents for both medical and non-medical radiation workers are given. A summary of the percentage of passes and failures of the final examination given at the end of each training course is also given. The present status of licensing for radiation facilities and workers is described, and its results are indicated. The successful control of ionizing radiation through this kind of intensive training and licensing is evidenced in the film badge records given by a centralized service laboratory located at the National Tsing Hua University. (author)
Zech, Astrid; Klahn, Philipp; Hoeft, Jon; Eulenburg, Christine Zu; Steib, Simon
Purpose Injury prevention effects of neuromuscular training have been partly attributed to postural control adaptations. Uncertainty exists regarding the magnitude of these adaptations and on how they can be adequately monitored. The objective was to determine the time course of neuromuscular traini
Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.
In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.
Sandip Meghnad Hulke
Full Text Available Context: Regular physical exercise is known to cause improvement of the cardiovascular function. This adaptation is studied here with the help of non-invasive methods. Aims: To evaluate morphological changes in heart by echocardiography, to see the effect of exercise on autonomic function, on aerobic power and to assess the sequence of changes. Settings and Design: Study comprises of 12-week duration and was done on the students of physical education. Materials and Methods: This study was a longitudinal study in which 100 subjects (51 male, 20.18 yrs±1.147, 49 female, 19.91 yrs±1.89 were assessed using electrocardiography, echocardiography and Queen′s College Step test (for VO 2max within 7 days of admission to their college and re-examined after 12 weeks. Statistical Analysis: Paired t-test using Graph pad prism5 software. Results: Electrocardiographic evaluation was suggestive of significant decrease in heart rate, significant increase in RR interval and t-wave amplitude in cardiac leads in males and similar but not significant result in females. No significant change was found in left ventricular morphology and ejection fraction after exercise program. Conclusions: The results of this study suggest that the exercise training over a period of 3 months does not influence cardiovascular morphology, but causes changes in parasympathetic and sympathetic tone and improves aerobic power.
Johanna Renny Octavia
Full Text Available Any rehabilitation involves people who are unique individuals with their own characteristics and rehabilitation needs, including patients suffering from Multiple Sclerosis (MS. The prominent variation of MS symptoms and the disease severity elevate a need to accommodate the patient diversity and support adaptive personalized training to meet every patient’s rehabilitation needs. In this paper, we focus on integrating adaptivity and personalization in rehabilitation training for MS patients. We introduced the automatic adjustment of difficulty levels as an adaptation that can be provided in individual and collaborative rehabilitation training exercises for MS patients. Two user studies have been carried out with nine MS patients to investigate the outcome of this adaptation. The findings showed that adaptive personalized training trajectories have been successfully provided to MS patients according to their individual training progress, which was appreciated by the patients and the therapist. They considered the automatic adjustment of difficulty levels to provide more variety in the training and to minimize the therapists involvement in setting up the training. With regard to social interaction in the collaborative training exercise, we have observed some social behaviors between the patients and their training partner which indicated the development of social interaction during the training.
Gómez, E.; A. S. Poznyak; Lozano, R, R.
Existen en la literatura de Control Adaptable, diferentes procedimientos en los que es posible identificar un sistema lineal. El problema fundamental es que una cantidad importante de fenómenos de la vida real son de tipo no lineal y no es tan sencillo el modelar este tipo de dinámicas. En este trabajo se presenta una forma de identificar sistemas no lineales utilizando las propiedades de las Redes Neuronales Artificiales y las técnicas de Algoritmo Genético en la optimización de ...
Heydari, Ali; Balakrishnan, Sivasubramanya N
To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.
Anguera, J A; Boccanfuso, J; Rintoul, J L; Al-Hashimi, O; Faraji, F; Janowich, J; Kong, E; Larraburo, Y; Rolle, C; Johnston, E; Gazzaley, A
Cognitive control is defined by a set of neural processes that allow us to interact with our complex environment in a goal-directed manner. Humans regularly challenge these control processes when attempting to simultaneously accomplish multiple goals (multitasking), generating interference as the result of fundamental information processing limitations. It is clear that multitasking behaviour has become ubiquitous in today's technologically dense world, and substantial evidence has accrued regarding multitasking difficulties and cognitive control deficits in our ageing population. Here we show that multitasking performance, as assessed with a custom-designed three-dimensional video game (NeuroRacer), exhibits a linear age-related decline from 20 to 79 years of age. By playing an adaptive version of NeuroRacer in multitasking training mode, older adults (60 to 85 years old) reduced multitasking costs compared to both an active control group and a no-contact control group, attaining levels beyond those achieved by untrained 20-year-old participants, with gains persisting for 6 months. Furthermore, age-related deficits in neural signatures of cognitive control, as measured with electroencephalography, were remediated by multitasking training (enhanced midline frontal theta power and frontal-posterior theta coherence). Critically, this training resulted in performance benefits that extended to untrained cognitive control abilities (enhanced sustained attention and working memory), with an increase in midline frontal theta power predicting the training-induced boost in sustained attention and preservation of multitasking improvement 6 months later. These findings highlight the robust plasticity of the prefrontal cognitive control system in the ageing brain, and provide the first evidence, to our knowledge, of how a custom-designed video game can be used to assess cognitive abilities across the lifespan, evaluate underlying neural mechanisms, and serve as a powerful tool
Frost, Susan A.; Balas, Mark J.
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.
Selinger, Jessica C; Donelan, J Maxwell
We have designed and tested a myoelectric controller that automatically adapts energy harvesting from the motion of leg joints to match the power available in different walking conditions. To assist muscles in performing negative mechanical work, the controller engages power generation only when estimated joint mechanical power is negative. When engaged, the controller scales its resistive torque in proportion to estimated joint torque, thereby automatically scaling electrical power generation in proportion to the available mechanical power. To produce real-time estimates of joint torque and mechanical power, the controller leverages a simple model that predicts these variables from measured muscle activity and joint angular velocity. We first tested the model using available literature data for a range of walking speeds and found that estimates of knee joint torque and power well match the corresponding literature profiles (torque R(2): 0.73-0.92; power R(2): 0.60-0.94). We then used human subject experiments to test the performance of the entire controller. Over a range of steady state walking speeds and inclines, as well as a number of non-steady state walking conditions, the myoelectric controller accurately identified when the knee generated negative mechanical power, and automatically adjusted the magnitude of electrical power generation. PMID:26841402
Åkerström, Thorbjörn; Fischer, Christian P; Plomgaard, Peter;
extensor training. They trained one leg while ingesting a 6% glucose solution (Glc) and ingested a sweetened placebo while training the other leg (Plc). The subjects trained their respective legs 2 h at a time on alternate days 5 days a week. Endurance training increased peak power (P(max)) and time...... to fatigue at 70% of P(max) approximately 14% and approximately 30%, respectively. CS and beta-HAD activity increased and glycogen content was greater after training, but there were no differences between Glc and Plc. After training the rate of oxidation of palmitate (R(ox)) and the % of rate...... of disappearance that was oxidized (%R(dox)) changed. %R(dox) was on average 16.4% greater during exercise after training whereas, after exercise %R(dox) was 30.4% lower. R(ox) followed the same pattern. However, none of these parameters were different between Glc and Plc. We conclude that glucose ingestion during...
Full Text Available Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link or 3 (Transport. In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MPEG-4 are used as the audio and video codec respectively. The proposed algorithm for adaptive quality control of audio communication is based on forward error correction (FEC. In the case of video communication, the proposed algorithm adapts the value of key frame interval, which is an encoding parameter of MPEG-4. We evaluated our proposed algorithms by computer simulation. We have shown that, in most cases, the proposed scheme gained a higher throughput compared to other schemes.
Balas, Mark J.; Frost, Susan
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.
Drake, Joshua C; Wilson, Rebecca J; Yan, Zhen
Exercise training enhances physical performance and confers health benefits, largely through adaptations in skeletal muscle. Mitochondrial adaptation, encompassing coordinated improvements in quantity (content) and quality (structure and function), is increasingly recognized as a key factor in the beneficial outcomes of exercise training. Exercise training has long been known to promote mitochondrial biogenesis, but recent work has demonstrated that it has a profound impact on mitochondrial dynamics (fusion and fission) and clearance (mitophagy), as well. In this review, we discuss the various mechanisms through which exercise training promotes mitochondrial quantity and quality in skeletal muscle.
Henningsen, Arne; Ravn, Ole
A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...
Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)
Hayder S. Abd Al-Amir
Full Text Available An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO. The structure of the controller consists of two models :the modified Elman neural network (MENN and the feed forward multi-layer Perceptron (MLP. The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. The feed forward neural controller is trained off-line and adaptive weights are implemented on-line to find the flap angles, which controls the plunge and pitch motion of the wing. The general back propagation algorithm is used to learn the feed forward neural controller and the neural identifier. The simulation results show the effectiveness of the proposed control algorithm; this is demonstrated by the minimized tracking error to zero approximation with very acceptable settling time even with the existence of bounded external disturbances.
Kedar-Dongarkar, Gurunath; Weslati, Feisel
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.
Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.
Ivlev, B I
Process of quantum tunneling of particles in various physical systems can be effectively controlled even by a weak and slow varying in time electromagnetic signal if to adapt specially its shape to a particular system. During an under-barrier motion of a particle such signal provides a "coherent" assistance of tunneling by the multi-quanta absorption resulting in a strong enhancement of the tunneling probability. The semiclassical approach based on trajectories in the complex time is developed for tunneling in a non-stationary field. Enhancement of tunneling occurs when a singularity of the signal coincides in position at the complex time plane with a singularity of the classical Newtonian trajectory of the particle. The developed theory is also applicable to the over-barrier reflection of particles and to reflection of classical waves (electromagnetic, hydrodynamic, etc.) from a spatially-smooth medium.
Schoenfeld, Brad J; Ratamess, Nicholas A; Peterson, Mark D; Contreras, Bret; Sonmez, G T; Alvar, Brent A
Regimented resistance training has been shown to promote marked increases in skeletal muscle mass. Although muscle hypertrophy can be attained through a wide range of resistance training programs, the principle of specificity, which states that adaptations are specific to the nature of the applied stimulus, dictates that some programs will promote greater hypertrophy than others. Research is lacking, however, as to the best combination of variables required to maximize hypertophic gains. The purpose of this study was to investigate muscular adaptations to a volume-equated bodybuilding-type training program vs. a powerlifting-type routine in well-trained subjects. Seventeen young men were randomly assigned to either a hypertrophy-type resistance training group that performed 3 sets of 10 repetition maximum (RM) with 90 seconds rest or a strength-type resistance training (ST) group that performed 7 sets of 3RM with a 3-minute rest interval. After 8 weeks, no significant differences were noted in muscle thickness of the biceps brachii. Significant strength differences were found in favor of ST for the 1RM bench press, and a trend was found for greater increases in the 1RM squat. In conclusion, this study showed that both bodybuilding- and powerlifting-type training promote similar increases in muscular size, but powerlifting-type training is superior for enhancing maximal strength.
Schoenfeld, Brad J; Ratamess, Nicholas A; Peterson, Mark D; Contreras, Bret; Sonmez, G T; Alvar, Brent A
Regimented resistance training has been shown to promote marked increases in skeletal muscle mass. Although muscle hypertrophy can be attained through a wide range of resistance training programs, the principle of specificity, which states that adaptations are specific to the nature of the applied stimulus, dictates that some programs will promote greater hypertrophy than others. Research is lacking, however, as to the best combination of variables required to maximize hypertophic gains. The purpose of this study was to investigate muscular adaptations to a volume-equated bodybuilding-type training program vs. a powerlifting-type routine in well-trained subjects. Seventeen young men were randomly assigned to either a hypertrophy-type resistance training group that performed 3 sets of 10 repetition maximum (RM) with 90 seconds rest or a strength-type resistance training (ST) group that performed 7 sets of 3RM with a 3-minute rest interval. After 8 weeks, no significant differences were noted in muscle thickness of the biceps brachii. Significant strength differences were found in favor of ST for the 1RM bench press, and a trend was found for greater increases in the 1RM squat. In conclusion, this study showed that both bodybuilding- and powerlifting-type training promote similar increases in muscular size, but powerlifting-type training is superior for enhancing maximal strength. PMID:24714538
Full Text Available Abstract Background Although robot therapy is progressively becoming an accepted method of treatment for stroke survivors, few studies have investigated how to adapt the robot/subject interaction forces in an automatic way. The paper is a feasibility study of a novel self-adaptive robot controller to be applied with continuous tracking movements. Methods The haptic robot Braccio di Ferro is used, in relation with a tracking task. The proposed control architecture is based on three main modules: 1 a force field generator that combines a non linear attractive field and a viscous field; 2 a performance evaluation module; 3 an adaptive controller. The first module operates in a continuous time fashion; the other two modules operate in an intermittent way and are triggered at the end of the current block of trials. The controller progressively decreases the gain of the force field, within a session, but operates in a non monotonic way between sessions: it remembers the minimum gain achieved in a session and propagates it to the next one, which starts with a block whose gain is greater than the previous one. The initial assistance gains are chosen according to a minimal assistance strategy. The scheme can also be applied with closed eyes in order to enhance the role of proprioception in learning and control. Results The preliminary results with a small group of patients (10 chronic hemiplegic subjects show that the scheme is robust and promotes a statistically significant improvement in performance indicators as well as a recalibration of the visual and proprioceptive channels. The results confirm that the minimally assistive, self-adaptive strategy is well tolerated by severely impaired subjects and is beneficial also for less severe patients. Conclusions The experiments provide detailed information about the stability and robustness of the adaptive controller of robot assistance that could be quite relevant for the design of future large scale
Rosendal, Lars; Langberg, Henning; Skov-Jensen, Arne;
Strenuous physical activity, such as military training, is known to demand a high degree of physical performance and to cause overuse injuries. However, the exact relation between injury incidence and physical fitness level and the influence of military training on measures of functional...
Jantzen, Jan; Poulsen, Niels Kjølstad
This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies...... an update mechanism similar to the SOC update mechanism. Two simulations of proportionally controlled systems show the behaviour of the proportional gain as it adapts to a specified behaviour....
Full Text Available Estimating the efficiency quotient in the competitionactivity of a sportsman facilitates the appreciation oftheir actual level of training. Basic data for researchingthe dynamics of the results are the control indicators.The results of the evaluation of the level of training onindicators of operative, current (present control, ofstage and final control allow realizing the individualcumulative indexes for each sportsman. In order toidentify the integrated index of the sportsmen’s training,it is necessary to cumulate the results of all the types ofcontrol. The aim of the study is to identify the practicalmethods to control and evaluate the individualcomponents of training, competition activity andintegrated level of training the sportsmen. The system oftypes of control suggested by the authors shows that thebasic data of studying the level of training of thesportsmen are indicators of initial evaluation. The totalof the sportsman’s results for all the types of controldetermines the individual cumulative index. Theformulas to calculate the integrated level of training andthe efficiency of the participation to competition of thesportsmen can identify their strong and weak points intraining, and according to them, make adaptations in thetraining curricula.Thus the control in the field of sports is an indicator ofthe level of sportsmen’s training, an instrument tooptimize the process of training and participation tocompetitions based on some objective evaluations of thedevelopment of the different qualities and of the integrallevel of training.
Full Text Available Research has shown that cognitive training can enhance performance in executive control tasks. Current study was designed to explore whether executive control can also be trained in adolescents, what particular aspects of executive control may underlie training and transfer effects, and whether acute bouts of exercise directly prior to cognitive training enhance training effects. For that purpose, a task switching training was employed that has been shown to be effective in other age groups. A group of adolescents (10-14 years, n = 20 that received a three-week TS training was compared to a group (n = 20 that received the same TS training but who exercised on a stationary bike before each training session. Additionally, a no-contact and an exercise-only control group were included (both ns = 20. Analyses indicated that both training groups significantly reduced their switching costs over the course of the training sessions and also reduced their mixing costs in a near transfer task. The reduction in mixing costs in the near transfer task was larger in the trained groups than in the non-trained control groups. Far transfer of cognitive training was limited to a choice reaction time task and a tendency for faster reaction times in an updating task. Findings indicate that executive control can be enhanced in adolescents through training and that updating may be of particular relevance for the effects of task switching training.
Prabhu, K; V. Murali Bhaskaran
Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...
Full Text Available Abstract Purpose Methoxyisoflavone (M, 20-hydroxyecdysone (E, and sulfo-polysaccharide (CSP3 have been marketed to athletes as dietary supplements that can increase strength and muscle mass during resistance-training. However, little is known about their potential ergogenic value. The purpose of this study was to determine whether these supplements affect training adaptations and/or markers of muscle anabolism/catabolism in resistance-trained athletes. Methods Forty-five resistance-trained males (20.5 ± 3 yrs; 179 ± 7 cm, 84 ± 16 kg, 17.3 ± 9% body fat were matched according to FFM and randomly assigned to ingest in a double blind manner supplements containing either a placebo (P; 800 mg/day of M; 200 mg of E; or, 1,000 mg/day of CSP3 for 8-weeks during training. At 0, 4, and 8-weeks, subjects donated fasting blood samples and completed comprehensive muscular strength, muscular endurance, anaerobic capacity, and body composition analysis. Data were analyzed by repeated measures ANOVA. Results No significant differences (p > 0.05 were observed in training adaptations among groups in the variables FFM, percent body fat, bench press 1 RM, leg press 1 RM or sprint peak power. Anabolic/catabolic analysis revealed no significant differences among groups in active testosterone (AT, free testosterone (FT, cortisol, the AT to cortisol ratio, urea nitrogen, creatinine, the blood urea nitrogen to creatinine ratio. In addition, no significant differences were seen from pre to post supplementation and/or training in AT, FT, or cortisol. Conclusion Results indicate that M, E, and CSP3 supplementation do not affect body composition or training adaptations nor do they influence the anabolic/catabolic hormone status or general markers of catabolism in resistance-trained males.
Butler, Ashley M.; Titus, Courtney
This article reviews the literature reporting engagement (enrollment, attendance, and attrition) in culturally adapted parent training for disruptive behavior among racial/ethnic minority parents of children ages 2 to 7 years. The review describes the reported rates of engagement in adapted interventions and how engagement is analyzed in studies,…
Thijssen, D.H.J.; Heesterbeek, P.; Kuppevelt, D. van; Duysens, J.E.J.; Hopman, M.T.E.
PURPOSE: Studies investigating vascular adaptations in non-exercised areas during whole body exercise training show conflicting results. Individuals with spinal cord injury (SCI) provide a unique model to examine vascular adaptations in active tissue vs adjacent inactive areas. The purpose of this s
Hounsgaard, Lise; Hansen, J. P.; Østergaard, B.;
BACKGROUND: Cognitive adaptation training (CAT) targets the adaptive behaviour of patients with schizophrenia and has shown promising results regarding the social aspects of psychosocial treatment. As yet, no reports have appeared on the use of CAT in combination with assertive community treatment...
Wei Wei; Li Dong-Hai; Wang Jing
The chaos control of uncertain unified chaotic systems is considered. Cascade adaptive control approach with only one control input is presented to stabilize states of the uncertain unified chaotic system at the zero equilibrium point.Since an adaptive controller based on dynamic compensation mechanism is employed, the exact model of the unified chaotic system is not necessarily required.By choosing appropriate controller parameters, chaotic phenomenon can be suppressed and the response speed is tunable. Sufficient condition for the asymptotic stability of the approach is derived. Numerical simulation results confirm that the cascade adaptive control approach with only one control signal is valid in chaos control of uncertain unified chaotic systems.
Fleck, Stephen J.; Kraerner, William J.
Resistance training causes a variety of physiological reactions, including changes in muscle size, connective tissue size, and bone mineral content. This article summarizes data from a variety of studies and research. (JL)
van Nort, Douglas
parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.
Andersen, T.O.; Hansen, M.R.; Conrad, Finn
A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation con...... joint behaves as an independent second-order system with fixed dynamics.......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...... control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each...
Satoh, Yasuyuki; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu
In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...
Grzegorz Mikułowski; Łukasz Jankowski
An adaptive landing gear is a landing gear (LG) capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~va...
Juntao Fei; Hongfei Ding
This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...
Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.
Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro
This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl
BLANCH Carolina; POLLIN Sofie; LAFRUIT Gauthier; EBERLE Wolfgang
Low energy consumption is one of the main challenges for wireless video transmission on battery limited devices. The energy invested at the lower layers of the protocol stack involved in data communication, such as link and physical layer, represent an important part of the total energy consumption. This communication energy highly depends on the channel conditions and on the transmission data rate. Traditionally, video coding is unaware of varying channel conditions. In this paper, we propose a cross-layer approach in which the rate control mechanism of the video codec becomes channel-aware and steers the instantaneous output rate according to the channel conditions to reduce the communication energy. Our results show that energy savings of up to30% can be obtained with a reduction of barely 0.1 dB on the average video quality. The impact of feedback delays is shown to be small. In addition, this adaptive mechanism has low complexity, which makes it suitable for real-time applications.
Bartlett, Jonathan D; Hawley, John A; Morton, James P
Traditional nutritional approaches to endurance training have typically promoted high carbohydrate (CHO) availability before, during and after training sessions to ensure adequate muscle substrate to meet the demands of high daily training intensities and volumes. However, during the past decade, data from our laboratories and others have demonstrated that deliberately training in conditions of reduced CHO availability can promote training-induced adaptations of human skeletal muscle (i.e. increased maximal mitochondrial enzyme activities and/or mitochondrial content, increased rates of lipid oxidation and, in some instances, improved exercise capacity). Such data have led to the concept of 'training low, but competing high' whereby selected training sessions are completed in conditions of reduced CHO availability (so as to promote training adaptation), but CHO reserves are restored immediately prior to an important competition. The augmented training response observed with training-low strategies is likely regulated by enhanced activation of key cell signalling kinases (e.g. AMPK, p38MAPK), transcription factors (e.g. p53, PPARδ) and transcriptional co-activators (e.g. PGC-1α), such that a co-ordinated up-regulation of both the nuclear and mitochondrial genomes occurs. Although the optimal practical strategies to train low are not currently known, consuming additional caffeine, protein, and practising CHO mouth-rinsing before and/or during training may help to rescue the reduced training intensities that typically occur when 'training low', in addition to preventing protein breakdown and maintaining optimal immune function. Finally, athletes should practise 'train-low' workouts in conjunction with sessions undertaken with normal or high CHO availability so that their capacity to oxidise CHO is not blunted on race day.
Bartlett, Jonathan D; Hawley, John A; Morton, James P
Traditional nutritional approaches to endurance training have typically promoted high carbohydrate (CHO) availability before, during and after training sessions to ensure adequate muscle substrate to meet the demands of high daily training intensities and volumes. However, during the past decade, data from our laboratories and others have demonstrated that deliberately training in conditions of reduced CHO availability can promote training-induced adaptations of human skeletal muscle (i.e. increased maximal mitochondrial enzyme activities and/or mitochondrial content, increased rates of lipid oxidation and, in some instances, improved exercise capacity). Such data have led to the concept of 'training low, but competing high' whereby selected training sessions are completed in conditions of reduced CHO availability (so as to promote training adaptation), but CHO reserves are restored immediately prior to an important competition. The augmented training response observed with training-low strategies is likely regulated by enhanced activation of key cell signalling kinases (e.g. AMPK, p38MAPK), transcription factors (e.g. p53, PPARδ) and transcriptional co-activators (e.g. PGC-1α), such that a co-ordinated up-regulation of both the nuclear and mitochondrial genomes occurs. Although the optimal practical strategies to train low are not currently known, consuming additional caffeine, protein, and practising CHO mouth-rinsing before and/or during training may help to rescue the reduced training intensities that typically occur when 'training low', in addition to preventing protein breakdown and maintaining optimal immune function. Finally, athletes should practise 'train-low' workouts in conjunction with sessions undertaken with normal or high CHO availability so that their capacity to oxidise CHO is not blunted on race day. PMID:24942068
Full Text Available The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill present and future aircraft safety objectives though automated vehicle recovery while maintaining performance and...
LIU Hai-ou; CHEN Hui-yan; DING Hua-rong; HE Zhong-bo
Based on detail analysis of clutch engaging process control targets and adaptive demands, a control strategy which is based on speed signal, different from that of based on main clutch displacement signal, is put forward. It considers both jerk and slipping work which are the most commonly used quality evaluating indexes of vehicle starting phase. The adaptive control system and its reference model are discussed profoundly.Taking the adaptability to different starting gears and different road conditions as examples, some proving field test records are shown to illustrate the main clutch adaptive control strategy at starting phase. Proving field test gives acceptable results.
National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...
Taleb, M.; Plestan, F.
This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results.
Verschure, Paul F M J
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID
Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.
The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....
Martinez, Charles R; Eddy, J Mark
A randomized experimental test of the implementation feasibility and the efficacy of a culturally adapted Parent Management Training intervention was conducted with a sample of 73 Spanish-speaking Latino parents with middle-school-aged youth at risk for problem behaviors. Intervention feasibility was evaluated through weekly parent satisfaction ratings, intervention participation and attendance, and overall program satisfaction. Intervention effects were evaluated by examining changes in parenting and youth adjustment for the intervention and control groups between baseline and intervention termination approximately 5 months later. Findings provided strong evidence for the feasibility of delivering the intervention in a larger community context. The intervention produced benefits in both parenting outcomes (i.e., general parenting, skill encouragement, overall effective parenting) and youth outcomes (i.e., aggression, externalizing, likelihood of smoking and use of alcohol, marijuana, and other drugs). Differential effects of the intervention were based on youth nativity status. PMID:16287384
Zhang, Qin; Xiong, Caihua; Chen, Wenbin
Surface Electromyography (EMG) is popularly used to decode human motion intention for robot movement control. Traditional motion decoding method uses pattern recognition to provide binary control command which can only move the robot as predefined limited patterns. In this work, we proposed a motion decoding method which can accurately estimate 3-dimensional (3-D) continuous upper limb motion only from multi-channel EMG signals. In order to prevent the muscle activities from motion artifacts and muscle crosstalk which especially obviously exist in upper limb motion, the independent component analysis (ICA) was applied to extract the independent source EMG signals. The motion data was also transferred from 4-manifold to 2-manifold by the principle component analysis (PCA). A hidden Markov model (HMM) was proposed to decode the motion from the EMG signals after the model trained by an adaptive model identification process. Experimental data were used to train the decoding model and validate the motion decoding performance. By comparing the decoded motion with the measured motion, it is found that the proposed motion decoding strategy was feasible to decode 3-D continuous motion from EMG signals.
Andrew L. SHIM
Full Text Available Objective: The purpose of this study was to assess range of motion adaptations in amateur tennis players based on the effects of a five week strength training program on the dominant and non-dominant arm. Subjects: An experimental and control group of six collegiate women tennis players (Div II and NAIA participated. After initial assessment, six subjects participated in a five week, four times a week, pre-season strength training program consisting of five exercises: External Rotation 90°, Seated Row, Scaption, Chest Press, and External Shoulder Rotation (Rubber tubing. Results: Data analysis through a paired t-test showed that there were no significant changes in ROM in the experimental group when compared to the control group. In conclusion, a strength training program is highly recommended for female overhead athletes combined with a proper flexibility regimen to promote best practice.
Keating, P; Rosenior-Patten, O.; Dahmen, J. C.; Bell, O.; King, A. J.
eLife digest The brain normally compares the timing and intensity of the sounds that reach each ear to work out a sound’s origin. Hearing loss in one ear disrupts these between-ear comparisons, which causes listeners to make errors in this process. With time, however, the brain adapts to this hearing loss and once again learns to localize sounds accurately. Previous research has shown that young ferrets can adapt to hearing loss in one ear in two distinct ways. The ferrets either learn to rem...
Nguyen, Charles C.; Antrazi, Sami S.
The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.
Taeed, Fazel; Nymand, Morten
An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations...... in converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter...
Sun, B.; Salter, P. S.; Booth, M. J.
The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.
Thijssen, D.H.J.; Groot, P.C.; Smits, P.; Hopman, M.T.E.
AIM: Because age-related changes in the large conduit arteries (increased wall thickness, and attenuated arterial compliance and endothelial function) are associated with cardiovascular pathology, prevention is of paramount importance. The effects of endurance training (i.e. walking or cycling) in o
For most elite athletes winning an Olympic gold medal is the ultimate dream. To make this dream come true, in the first place one needs sufficient talent. However next to this talent, several years of training with large amounts of strenuous work is necessary. It is therefore not remarkable that the
Ginneken, Mireille Maria Elisabeth van
In the present thesis the localization and activation of signaling proteins, known from human studies, in equine muscle were investigated under conditions of rest, after an acute bout of exercise and before and after a period of (intensified) training. Proteins of interest (protein kinase C (PKC), m
Tinken, T.M.; Thijssen, D.H.J.; Hopkins, N.; Dawson, E.A.; Cable, N.T.; Green, D.J.
Although episodic changes in shear stress have been proposed as the mechanism responsible for the effects of exercise training on the vasculature, this hypothesis has not been directly addressed in humans. We examined brachial artery flow-mediated dilation, an index of NO-mediated endothelial functi
Mizuno, M; Juel, C; Bro-Rasmussen, Thomas;
Morphological and biochemical characteristics of biopsies obtained from gastrocnemius (GAS) and triceps brachii muscle (TRI), as well as maximal O2 uptake (VO2 max) and O2 deficit, were determined in 10 well-trained cross-country skiers before and after a 2-wk stay (2,100 m above sea level) and t...
Full Text Available In this paper, an adaptive controller is designed for a UAV flight control system against faults and parametric uncertainties based on quantum information technology and the Popov hyperstability theory. First, considering the bounded control input, the state feedback controller is designed to make the system stable. The model of adaptive control is introduced to eliminate the impact by the uncertainties of system parameters via quantum information technology. Then, according to the model reference adaptive principle, an adaptive control law based on the Popov hyperstability theory is designed. This law enable better robustness of the flight control system and tracking control performances. The closed‐loop system’s stability is guaranteed by the Popov hyperstability theory. The simulation results demonstrate that a better dynamic performance of the UAV flight control system with faults and parametric uncertainties can be maintained with the proposed method.
The objective of this report is to provide NPP managers, training center managers and personnel involved with control room simulator training with practical information they can use to improve the performance of their personnel. While the emphasis in this report is on simulator training of control room personnel using full scope simulators, information is also provided on how organizations have effectively used control room simulators for training of other NPP Personnel, Vienna (AT) including simulators other than full-scope simulators. The documents includes: the main body with current practices and recommendations; selected examples from countries; a CD ROM with all examples (different languages). The document will be available on the IAEA web site. The topics describes are: trends in simulators training; designing and developing training involving room simulators; implementation of simulator training; evaluating the effectiveness of simulator training; simulator instructor competence; application of different types of simulators in the training of NPP personnel (other than full scope simulators
ZHANG Yanxia; GUO Lei
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.
National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...
Plews, Daniel J; Laursen, Paul B; Stanley, Jamie; Kilding, Andrew E; Buchheit, Martin
The measurement of heart rate variability (HRV) is often considered a convenient non-invasive assessment tool for monitoring individual adaptation to training. Decreases and increases in vagal-derived indices of HRV have been suggested to indicate negative and positive adaptations, respectively, to endurance training regimens. However, much of the research in this area has involved recreational and well-trained athletes, with the small number of studies conducted in elite athletes revealing equivocal outcomes. For example, in elite athletes, studies have revealed both increases and decreases in HRV to be associated with negative adaptation. Additionally, signs of positive adaptation, such as increases in cardiorespiratory fitness, have been observed with atypical concomitant decreases in HRV. As such, practical ways by which HRV can be used to monitor training status in elites are yet to be established. This article addresses the current literature that has assessed changes in HRV in response to training loads and the likely positive and negative adaptations shown. We reveal limitations with respect to how the measurement of HRV has been interpreted to assess positive and negative adaptation to endurance training regimens and subsequent physical performance. We offer solutions to some of the methodological issues associated with using HRV as a day-to-day monitoring tool. These include the use of appropriate averaging techniques, and the use of specific HRV indices to overcome the issue of HRV saturation in elite athletes (i.e., reductions in HRV despite decreases in resting heart rate). Finally, we provide examples in Olympic and World Champion athletes showing how these indices can be practically applied to assess training status and readiness to perform in the period leading up to a pinnacle event. The paper reveals how longitudinal HRV monitoring in elites is required to understand their unique individual HRV fingerprint. For the first time, we demonstrate how
Jiangyan ZHANG; Xiaohong JIAO
In this paper, the control problem of auxiliary power unit (APU) for hybrid electric vehicles is investigated. An adaptive controller is provided to achieve the coordinated control between the engine speed and the battery charging voltage. The proposed adaptive coordinated control laws for the throttle angle of the engine and the voltage of the power-converter can guarantee not only the asymptotic tracking performance of the engine speed and the regulation of the battery charging voltage, but also the robust stability of the closed loop system under external load changes. Simulation results are given to verify the performance of the proposed adaptive controller.
Xiao-juan WU; Xin-jian ZHU; Guang-yi CAO; Heng-yong TU
The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.
For most elite athletes winning an Olympic gold medal is the ultimate dream. To make this dream come true, in the first place one needs sufficient talent. However next to this talent, several years of training with large amounts of strenuous work is necessary. It is therefore not remarkable that the time required for adequate recovery may easily be compromised. Doing so, an athlete is often challenging the optimal balance between exercise and recovery. The general purpose of this study was to...
Tinoco-Fernández, Maria; Jiménez-Martín, Miguel; Sánchez-Caravaca, M Angeles; Fernández-Pérez, Antonio M; Ramírez-Rodrigo, Jesús; Villaverde-Gutiérrez, Carmen
Although all authors report beneficial health changes following training based on the Pilates method, no explicit analysis has been performed of its cardiorespiratory effects. The objective of this study was to evaluate possible changes in cardiorespiratory parameters with the Pilates method. A total of 45 university students aged 18-35 years (77.8% female and 22.2% male), who did not routinely practice physical exercise or sports, volunteered for the study and signed informed consent. The Pilates training was conducted over 10 weeks, with three 1-hour sessions per week. Physiological cardiorespiratory responses were assessed using a MasterScreen CPX apparatus. After the 10-week training, statistically significant improvements were observed in mean heart rate (135.4-124.2 beats/min), respiratory exchange ratio (1.1-0.9) and oxygen equivalent (30.7-27.6) values, among other spirometric parameters, in submaximal aerobic testing. These findings indicate that practice of the Pilates method has a positive influence on cardiorespiratory parameters in healthy adults who do not routinely practice physical exercise activities. PMID:27357919
WANG Ping; YANG Ru-qing
A self-adaptive control method is proposed basedon an artificial neural network(ANN) with acceleratedevolutionary programming(AEP.) algorithm. The neuralnetwork is used to model the uncertainty process, fromwhich the teacher signals are produced online to regulate theparameters of the controller. The accelerated evolutionaryprogramming is used to train the neural network. Theexperiment results show that the method can obviouslyimprove the dynamic performance of uncertainty systems.
Anguera, Joaquin A; Bernard, Jessica A; Jaeggi, Susanne M; Buschkuehl, Martin; Benson, Bryan L; Jennett, Sarah; Humfleet, Jennifer; Reuter-Lorenz, Patricia A; Jonides, John; Seidler, Rachael D
We have recently demonstrated that visuospatial working memory performance predicts the rate of motor skill learning, particularly during the early phase of visuomotor adaptation. Here, we follow up these correlational findings with direct manipulations of working memory resources to determine the impact on visuomotor adaptation, a form of motor learning. We conducted two separate experiments. In the first one, we used a resource depletion strategy to investigate whether the rate of early visuomotor adaptation would be negatively affected by fatigue of spatial working memory resources. In the second study, we employed a dual n-back task training paradigm that has been shown to result in transfer effects  over five weeks to determine whether training-related improvements would boost the rate of early visuomotor adaptation. The depletion of spatial working memory resources negatively affected the rate of early visuomotor adaptation. However, enhancing working memory capacity via training did not lead to improved rates of visuomotor adaptation, suggesting that working memory capacity may not be the factor limiting maximal rate of visuomotor adaptation in young adults. These findings are discussed from a resource limitation/capacity framework with respect to current views of motor learning. PMID:22155489
Eklund, D; Pulverenti, T; Bankers, S; Avela, J; Newton, R; Schumann, M; Häkkinen, K
The present study investigated neuromuscular adaptations between same-session combined strength and endurance training with 2 loading orders and different day combined training over 24 weeks. 56 subjects were divided into different day (DD) combined strength and endurance training (4-6 d·wk(-1)) and same-session combined training: endurance preceding strength (E+S) or vice versa (S+E) (2-3 d·wk(-1)). Dynamic and isometric strength, EMG, voluntary activation, muscle cross-sectional area and endurance performance were measured. All groups increased dynamic one-repetition maximum (pmuscle cross-sectional area (ptraining (pmuscle actions. A high correlation (padaptations showed indications of being compromised and highly individual relating to changes in isometric strength when E+S-training was performed, while gains in one-repetition maximum, endurance performance and hypertrophy did not differ between the training modes.
Full Text Available Continues Stirred Tank Reactor (CSTR is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of CSTR than PID controller.
Wong, Y M; Ng, Gabriel
The present study examined and compared two modes of weight training (bodybuilding and power-lifting) on the surface EMG of vasti muscles, knee joint position sense and isometric knee extension force in 48 able-bodied subjects. Subjects were randomly allocated into either a moderate loading and repetitions (bodybuilding) training or a high loading and low repetitions (power-lifting) training, or a no training control group. Training was conducted on alternate days with individual supervision. After 8 weeks of training, subjects from both training groups showed significantly earlier EMG onset timing and higher amplitude of vastus medialis obliquus relative to vastus lateralis (p=0.005 or 0.05) between the two training groups. The findings suggested that the neuromotor control of the vasti muscles could be altered by regular weight training.
Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.
An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...
GUAN Ping; LIU Xiang-dong; CHEN Jia-bin; LIU Xiao-he
The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite.The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.
WUZhao-Jing; XIEXue-Jun; ZHANGSi-Ying
For a class of systems with unmodeled dynamics, robust adaptive stabilization problem is considered in this paper. Firstly， by a series of coordinate changes, the original system is reparameterized. Then, by introducing a reduced-order observer, an error system is obtained. Based on the system, a reduced-order adaptive backstepping controller design scheme is given. It is proved that all the signals in the adaptive control system are globally uniformly bounded, and the regulation error converges to zero asymptotically. Due to the order deduction of the controller, the design scheme in this paper has more practical values. A simulation example further demonstrates the efficiency of the control scheme.
In this paper, adaptive identification and control of nonlinear dynamical systems are investigated using radial basis function networks (RBF). Firstly, a novel approach to train the RBF is introduced, which employs an adaptive fuzzy generalized learning vector quantization (AFGLVQ) technique and recursive least squares algorithm with variable forgetting factor (VRLS). The AFGLVQ adjusts the centers of the RBF while the VRLS updates the connection weights of the network. The identification algorithm has the properties of rapid convergence and persistent adaptability that make it suitable for real-time control. Secondly, on the basis of the one-step ahead RBF predictor, the control law is optimized iteratively through a numerical stable Davidon's least squares-based (SDLS) minimization approach. Four nonlinear examples are simulated to demonstrate the effectiveness of the identification and control algorithms.
In practice, retraining a trained classifier is necessary when novel data become available. This paper adopts an incremental learning procedure to adaptively train a Kernel-based Nonlinear Representor(KNR), a recently presented nonlinear classifier for optimal pattern representation, so that its generalization ability may be evaluated in time-variant situation and a sparser representation is obtained for computationally intensive tasks. The addressed techniques are applied to handwritten digit classification to illustrate the feasibility for pattern recognition.
Ian A. Gravagne
Full Text Available It has been known for some time that proportional output feedback will stabilize MIMO, minimum-phase, linear time-invariant systems if the feedback gain is sufficiently large. High-gain adaptive controllers achieve stability by automatically driving up the feedback gain monotonically. More recently, it was demonstrated that sample-and-hold implementations of the high-gain adaptive controller also require adaptation of the sampling rate. In this paper, we use recent advances in the mathematical field of dynamic equations on time scales to unify and generalize the discrete and continuous versions of the high-gain adaptive controller. We prove the stability of high-gain adaptive controllers on a wide class of time scales.
Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...
Kim, J. D. [Cowell SysNet, Seoul (Korea); Lee, M. J.; Choi, Y. K.; Kim, S. S. [Pusan National University, Pusan (Korea)
This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory control of the two-link manipulator. (author). 18 refs., 14 figs., 2 tabs.
Donna-Jean P. Brock
Full Text Available Background: Programs that focus on positive parenting have been shown to improve parental attitudes, knowledge, and behaviors, and increase parent and child bonding. These programs are typically conducted in a closed group format. However, when individual or community needs are more immediate, programmers sometimes opt for an open group format. To determine the effectiveness of this adaptation to an open group format, the present study compared both groups on parental outcomes. Methods: Both closed and open group formats were offered and implemented between January 2009 and December 2012. Participants for both formats were recruited through similar means and the format placement for each family was determined by the immediacy of the need for an intervention, the time lapse until a new cycle would begin, and scheduling flexibility. Chi-Square analyses were conducted to determine demographic differences between the two groups and gain scores were calculated from the pre- and post-test AAPI-2 scales within a mixed MANOVA to determine group for-mat effectiveness. Results: Though open groups contained higher risk families; parental out-come improvements were significant for both groups. All participants, regardless of group membership, demonstrated the same statistically significant improvements following completion of the program. Conclusion: Findings provide support for adapting group formats when necessary to fit community and individual needs.
Johnson, Kathryn E.
Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.
Gibala, Martin J
Team sports are characterized by intermittent high-intensity activity patterns. Typically, play consists of short periods of very intense or all-out efforts interspersed with longer periods of low-intensity activity. Fatigue is a complex, multi-factorial process, but intense intermittent exercise performance can potentially be limited by reduced availability of substrates stored in skeletal muscle and/or metabolic by-products associated with fuel breakdown. High-intensity interval training (HIT) has been shown to induce adaptations in skeletal muscle that enhance the capacity for both oxidative and non-oxidative metabolism. Nutrient availability is a potent modulator of many acute physiological responses to exercise, including various molecular signaling pathways that are believed to regulate cellular adaptation to training. Several nutritional strategies have also been reported to acutely alter metabolism and enhance intermittent high-intensity exercise performance. However, relatively little is known regarding the effect of chronic interventions, and whether supplementation over a period of weeks or months augments HIT-induced physiological remodeling and promotes greater performance adaptations. Theoretically, a nutritional intervention could augment HIT adaptation by improving energy metabolism during exercise, which could facilitate greater total work and an enhanced chronic training stimulus, or promoting some aspect of the adaptive response during recovery, which could lead to enhanced physiological adaptations over time.
This thesis concerns speed control of current vector controlled induction motor drives (CVC drives). The CVC drive is an existing prototype drive developed by Danfoss A/S, Transmission Division. Practical tests have revealed that the open loop dynamical properties of the CVC drive are highly......, (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...
© 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.
We give a formal specification for a real-time controller for trains that operate on the Italian railway network. The controller will control train movements and is part of a larger system destined to guarantee safety with respect to dangers originating from train traffic in the railway network. Based on an informal specification document from the Italian railway company, we construct a simple state-based model and formalise it in terms of the property-based specification language TRIO. The o...
... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Internal controls, procedures, and training... HOUSING AND URBAN DEVELOPMENT SAFETY AND SOUNDNESS MORTGAGE FRAUD REPORTING § 1731.5 Internal controls, procedures, and training. An Enterprise shall establish adequate and efficient internal controls...
Revitalisation thermal columns propulsion train control system is very urgent to be implemented because of the test results and observation, control system performance is not normal, there are several components that must be renewed. Components includes MCB, magnetic contactors, push buttons, indicator lights and wiring. Drive motor is used to power 1.5 kW 3 phase, 380 volts and 50 Hz, nominal current (In = 3.75 A). Thermal column is one of the irradiation facility at the Kartini reactor has a beam-shaped room of measuring 1.2 X 1.2 X 1.6 m contains graphite blocks 10.2 X 10.2 X 127 cm(1) and is tangentially connected to the Kartini reactor core. Graphite blocks mounted reflector extends from the outer side to the inner surface of the door closer. Door closer contains barite concrete as radiation shielding and can be moved forward and backward to close and to open using a rotating motor to spin the wheel transmission system for running on rails. (author)
Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben
This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...
Gunnarsson, Thomas; Christensen, Peter Møller; Holse, Kris;
PURPOSE: The present study examined the effect of additional speed-endurance training during the season on muscle adaptations and performance of trained soccer players. METHODS: Eighteen sub-elite soccer players performed one session with 6-9 30-s intervals at an intensity of 90-95 % ofmaximal...... intensity (speed endurance training; SET) a week for 5 weeks (SET-intervention). Before and after the SET-intervention the players carried out the Yo-Yo intermittent recovery level 2 (Yo- Yo IR2) test, a sprint test (10- and 30-m) and an agility test. In addition, seven of the players had a resting muscle...
Martín-Hernández, Juan; Ruiz-Aguado, Jorge; Herrero, Juan Azael;
The purpose of this study was to determine the adaptive response of ratings of perceived exertion (RPE) and pain over six consecutive training sessions. Thirty subjects were assigned to either a blood flow restricted training group (BFRT) or a high intensity group (HIT). BFRT group performed four.......01). No between-group differences were found at any time point. In summary, BFRT induces a high perceptual response to training. However, this perceptual response is rapidly attenuated, leading to values similar to those experienced during HIT. Low load BFRT should not be limited to highly motivated individuals...
Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan
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.
Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced s...
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Erik D. Engeberg
Full Text Available Eight human test subjects attempted to track a desired position trajectory with an instrumented manipulandum (MN. The test subjects used the MN with three different levels of stiffness. A transfer function was developed to represent the human application of a precision grip from the data when the test subjects initially displaced the MN so as to learn the position mapping from the MN onto the display. Another transfer function was formed from the data of the remainder of the experiments, after significant displacement of the MN occurred. Both of these transfer functions accurately modelled the system dynamics for a portion of the experiments, but neither was accurate for the duration of the experiments because the human grip dynamics changed while learning the position mapping. Thus, an adaptive system model was developed to describe the learning process of the human test subjects as they displaced the MN in order to gain knowledge of the position mapping. The adaptive system model was subsequently validated following comparison with the human test subject data. An examination of the average absolute error between the position predicted by the adaptive model and the actual experimental data yielded an overall average error of 0.34mm for all three levels of stiffness.
This volume provides lesson plans for training radiological control technicians. Covered here is basic radiological documentation, counting errors, dosimetry, environmental monitoring, and radiation instruments
Shan Lu; Shijie Xu
A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed. Lawden equation is used to describe relative motion of two spacecraft. Then an adaptive gain factor is introduced, and an adaptive control law for autonomous rendezvous on the elliptical orbit is designed using Lyapunov approach. The relative motion is proved to be ultimately bounded under this control law, and the final relative position error can achieve the expected magnitude. Simulation results indicate that the adaptive control law can realize autonomous rendezvous on the elliptical orbit with relative state information only.
Full Text Available Abstract This study examined whether supplementing the diet with a commercial supplement containing zinc magnesium aspartate (ZMA during training affects zinc and magnesium status, anabolic and catabolic hormone profiles, and/or training adaptations. Forty-two resistance trained males (27 ± 9 yrs; 178 ± 8 cm, 85 ± 15 kg, 18.6 ± 6% body fat were matched according to fat free mass and randomly assigned to ingest in a double blind manner either a dextrose placebo (P or ZMA 30–60 minutes prior to going to sleep during 8-weeks of standardized resistance-training. Subjects completed testing sessions at 0, 4, and 8 weeks that included body composition assessment as determined by dual energy X-ray absorptiometry, 1-RM and muscular endurance tests on the bench and leg press, a Wingate anaerobic power test, and blood analysis to assess anabolic/catabolic status as well as markers of health. Data were analyzed using repeated measures ANOVA. Results indicated that ZMA supplementation non-significantly increased serum zinc levels by 11 – 17% (p = 0.12. However, no significant differences were observed between groups in anabolic or catabolic hormone status, body composition, 1-RM bench press and leg press, upper or lower body muscular endurance, or cycling anaerobic capacity. Results indicate that ZMA supplementation during training does not appear to enhance training adaptations in resistance trained populations.
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.
Full Text Available Marie-Ludivine Chateau-Degat1, Gérard Papouin2, Philippe Saint-Val3, Antonio Lopez21Axe sante des populations et environmentale, CHUQ, Laval University, Quebec, Canada; 2Service de Cardiologie, Centre Hospitalier Territorial du Taone, 3Fédération Tahitienne de Karaté, Papeete, French PolynesiaBackground: Aging is associated with a decrease in physical skills, sometimes accompanied by a change in quality of life (QOL. Long-term martial arts practice has been proposed as an avenue to counter these deleterious effects. The general purpose of this pilot study was to identify the effects of an adapted karate training program on QOL, depression, and motor skills in 50-year-old men.Methods and design: Fifteen 50-year-old men were enrolled in a one-year prospective experiment. Participants practiced adapted karate training for 90 minutes three times a week. Testing sessions, involving completion of the MOS 36-item Short Form Health Survey (SF36 and Beck Depression Inventory, as well as motor and effort evaluation, were done at baseline, and six and 12 months.Results: Compared with baseline, participants had better Beck Depression Inventory scores after one year of karate training (P < 0.01 and better perception of their physical health (P < 0.01, but not on the mental dimension (P < 0.49. They also improved their reaction time scores for the nondominant hand and sway parameters in the eyes-closed position (P < 0.01.Conclusion: Regular long-term karate practice had favorable effects on mood, perception of physical health confirmed by better postural control, and improved performance on objective physical testing. Adapted karate training would be an interesting option for maintaining physical activity in aging.Keywords: karate, balance, training, sport, aging
Sonneveldt, L.; Van Oort, E.R.; Chu, Q.P.; Mulder, J.A.
In this paper a theoretical framework for nonlinear adaptive flight control is developed and applied to a simplified, over-actuated nonlinear fighter aircraft model. The framework is based on a modular adaptive backstepping scheme with a new type of nonlinear estimator. The nonlinear estimator is co
Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong
The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.
de Sousa Júnior, C; Hermerly, E M
A Neural Network - based control approach for mobile robot is proposed. The weight adaptation is made on-line, without previous learning. Several possible situations in robot navigation are considered, including uncertainties in the model and presence of disturbance. Weight adaptation laws are presented as well as simulation results.
Qi Zhidong; Zhu Xinjian; Cao Guangyi
Aiming at on-line controlling of Direct Methanol Fuel Cell (DMFC) stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an Adaptive Neural Fuzzy Inference System (ANFIS) identification model of DMFC stack temperature is developed based on the input-output sampled data, which can avoid the internal complexity of DMFC stack. In the controlling process, with the network model trained well as the reference model of the DMFC control system, a novel fuzzy genetic algorithm is used to regulate the parameters and fuzzy rules of a neural fuzzy controller. In the simulation, compared with the nonlinear Proportional Integral Derivative (PID) and traditional fuzzy algorithm, the improved neural fuzzy controller designed in this paper gets better performance, as demonstrated by the simulation results.
This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine
Costa, Mário J.; Balasekaran, Govindasamy; Vilas-Boas, J. Paulo; Barbosa, Tiago M.
The purpose of this systematic review was to summarize longitudinal studies on swimming physiology and get implications for daily practice. A computerized search of databases according to the PRISMA statement was employed. Studies were screened for eligibility on inclusion criteria: (i) present two testing points; (ii) on swimming physiology; (iii) using adult elite swimmers; (iv) no case-studies or with small sample sizes. Two independent reviewers used a checklist to assess the methodological quality of the studies. Thirty-four studies selected for analysis were gathered into five main categories: blood composition (n=7), endocrine secretion (n=11), muscle biochemistry (n=7), cardiovascular response (n=8) and the energetic profile (n=14). The mean quality index was 10.58 ± 2.19 points demonstrating an almost perfect agreement between reviewers (K = 0.93). It can be concluded that the mixed findings in the literature are due to the diversity of the experimental designs. Micro variables obtained at the cellular or molecular level are sensitive measures and demonstrate overtraining signs and health symptoms. The improvement of macro variables (i.e. main physiological systems) is limited and may depend on the athletes’ training background and experience. PMID:26839618
Costa Mário J.
Full Text Available The purpose of this systematic review was to summarize longitudinal studies on swimming physiology and get implications for daily practice. A computerized search of databases according to the PRISMA statement was employed. Studies were screened for eligibility on inclusion criteria: (i present two testing points; (ii on swimming physiology; (iii using adult elite swimmers; (iv no case-studies or with small sample sizes. Two independent reviewers used a checklist to assess the methodological quality of the studies. Thirty-four studies selected for analysis were gathered into five main categories: blood composition (n=7, endocrine secretion (n=11, muscle biochemistry (n=7, cardiovascular response (n=8 and the energetic profile (n=14. The mean quality index was 10.58 ± 2.19 points demonstrating an almost perfect agreement between reviewers (K = 0.93. It can be concluded that the mixed findings in the literature are due to the diversity of the experimental designs. Micro variables obtained at the cellular or molecular level are sensitive measures and demonstrate overtraining signs and health symptoms. The improvement of macro variables (i.e. main physiological systems is limited and may depend on the athletes’ training background and experience.
Kon, Michihiro; Ohiwa, Nao; Honda, Akiko; Matsubayashi, Takeo; Ikeda, Tatsuaki; Akimoto, Takayuki; Suzuki, Yasuhiro; Hirano, Yuichi; Russell, Aaron P
Hypoxia is an important modulator of endurance exercise-induced oxidative adaptations in skeletal muscle. However, whether hypoxia affects resistance exercise-induced muscle adaptations remains unknown. Here, we determined the effect of resistance exercise training under systemic hypoxia on muscular adaptations known to occur following both resistance and endurance exercise training, including muscle cross-sectional area (CSA), one-repetition maximum (1RM), muscular endurance, and makers of mitochondrial biogenesis and angiogenesis, such as peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α), citrate synthase (CS) activity, nitric oxide synthase (NOS), vascular endothelial growth factor (VEGF), hypoxia-inducible factor-1 (HIF-1), and capillary-to-fiber ratio. Sixteen healthy male subjects were randomly assigned to either a normoxic resistance training group (NRT, n = 7) or a hypoxic (14.4% oxygen) resistance training group (HRT, n = 9) and performed 8 weeks of resistance training. Blood and muscle biopsy samples were obtained before and after training. After training muscle CSA of the femoral region, 1RM for bench-press and leg-press, muscular endurance, and skeletal muscle VEGF protein levels significantly increased in both groups. The increase in muscular endurance was significantly higher in the HRT group. Plasma VEGF concentration and skeletal muscle capillary-to-fiber ratio were significantly higher in the HRT group than the NRT group following training. Our results suggest that, in addition to increases in muscle size and strength, HRT may also lead to increased muscular endurance and the promotion of angiogenesis in skeletal muscle. PMID:24907297
Thijssen, D.H.J.; Ellenkamp, R.; Smits, P.; Hopman, M.T.E.
OBJECTIVE: To assess the time course of arterial adaptations during 6 weeks of functional electric stimulation (FES) training and 6 weeks of detraining in subjects with spinal cord injury (SCI). DESIGN: Intervention study (before-after trial). SETTING: University medical center. PARTICIPANTS: Volunt
Kappen, H. J.; Ruiz, H. C.
Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.
Schulz, Richard; And Others
Research suggests that primary control increases as humans develop from infancy through middle age and then decreases in old age. To minimize losses, individuals rely on cognitively based secondary control processes in middle and old age. Literature on adult control processes is reviewed. (SLD)
Full Text Available Recently, a novel type of high-intensity interval training known as sprint interval training has demonstrated increases in aerobic and anaerobic performance with very low time commitment. However, this type of training program is unpractical for general populations. The present study compared the impact of a low-volume high-intensity interval training to a "all-out" sprint interval training. Twenty-four active young males were recruited and randomized into three groups: (G1: 3-5 cycling bouts × 30-s all-out with 4 min recovery; G2: 6- 10 cycling bouts × 125% Pmax with 2 min recovery and a non-trained control group. They all performed a VO2max test, a time to exhaustion at Pmax (Tmax and a Wingate test before and after the intervention. Capillary blood lactate was taken at rest, 3, and 20 min after the Wingate trial. Training was performed 3 sessions per week for 4 weeks. In G1, significant improvements (p < 0.05 following training were found in VO2max (9.6%, power at VO2max (12.8%, Tmax (48.4%, peak power output (10.3% and mean power output (17.1%. In G2, significant improvements following training were found in VO2max (9.7%, power at VO2max (16.1%, Tmax (54.2%, peak power output (7.4%; p < 0.05, but mean power output did not change significantly. Blood lactate recovery (20th min significantly decreased in G1 and G2 when compared with pre-testing and the CON group (p < 0.05. In conclusion, the results of the current study agree with earlier work demonstrating the effectiveness of 30-s all-out training program to aerobic and anaerobic adaptations. Of substantial interest is that the low volume high intensity training provides similar results but involves only half the intensity with double the repetitions
Siu, Ka-Chun; Best, Bradley J; Kim, Jong Wook; Oleynikov, Dmitry; Ritter, Frank E
The Department of Defense has pursued the integration of virtual reality simulation into medical training and applications to fulfill the need to train 100,000 military health care personnel annually. Medical personnel transitions, both when entering an operational area and returning to the civilian theater, are characterized by the need to rapidly reacquire skills that are essential but have decayed through disuse or infrequent use. Improved efficiency in reacquiring such skills is critical to avoid the likelihood of mistakes that may result in mortality and morbidity. We focus here on a study testing a theory of how the skills required for minimally invasive surgery for military surgeons are learned and retained. Our adaptive virtual reality surgical training system will incorporate an intelligent mechanism for tracking performance that will recognize skill deficiencies and generate an optimal adaptive training schedule. Our design is modeling skill acquisition based on a skill retention theory. The complexity of appropriate training tasks is adjusted according to the level of retention and/or surgical experience. Based on preliminary work, our system will improve the capability to interactively assess the level of skills learning and decay, optimizes skill relearning across levels of surgical experience, and positively impact skill maintenance. Our system could eventually reduce mortality and morbidity by providing trainees with the reexperience they need to help make a transition between operating theaters. This article reports some data that will support adaptive tutoring of minimally invasive surgery and similar surgical skills. PMID:27168575
Lin, Chih-Min; Peng, Ya-Fu
An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993
Alex M C Smith
Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
JIANG Rui; LUO Guiming
The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.
李洪兴; 苗志宏; 王家银
This paper focuses on the control problem of the quadruple inverted pendulum by variable universe adaptive fuzzy control.First,the mathematical model on the quadruple inverted pendulum is described and its controllability is versified.Then,an efficient controller on the quadruple inverted pendulum is designed by using variable universe adaptive fuzzy control theory.Finally the simulation of the quadruple inverted pendulum is shown in detail.Besides,the experimental results on the hardware systems,i.e.real object systems,on a single inverted pendulum,a double inverted pendulum and a triple inverted pendulum are briefly introduced.``
Yaonan WANG; Jinzhu PENG; Wei SUN; Hongshan YU; Hui ZHANG
To deal with the uncertainty factors of robotic systems,a robust adaptive tracking controller is Droposed.The knowledge of the uncertainty factors is assumed to be unidentified;the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded,immeasurable disturbances entering the System.The stability of the proposed controller is proven by the Lyapunov method.The proposed controller can easily be implemented and the stability of the closed system can be ensured;the tracking error and adaptation parameter error are uniformly ultimately bounded(UUB).Finally,some simulation examples are utilized to illustrate the control performance.
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...
National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...
National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system...
National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...
LI; KePing; GAO; ZiYou; YANG; LiXing
Train control system plays a key role in railway traffic. Its function is to manage and control the train movement on railway networks. In our previous works, based on the cellular automata (CA) model, we proposed several models and algorithms for simulating the train movement under different control system conditions. However, these models are only suitable for some simple traffic conditions. Some basic factors, which are important for train movement, are not considered. In this paper, we extend these models and algorithms and give a unified formula. Using the proposed method, we analyze and discuss the space-time diagram of railway traffic flow and the trajectories of the train movement. The numerical simulation and analytical results demonstrate that the unified CA model is an effective tool for simulating the train control system.
Nguyen, Nhan T.
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.
Koopman, B.; Meuleman, J.H.; Asseldonk, van E.H.F.; Kooij, van der H.
For the rehabilitation of neurological patients robot-aided gait training is increasingly being used. Lack of balance training in these robotic gait trainers might contribute to the fact that they do not live up to the expectations. Therefore, in this study we developed and evaluated an algorithm to
Helge, Jørn Wulff
To investigate the effect of prolonged adaptation to training and fat- or carbohydrate-rich diet on body composition and insulin resistance.......To investigate the effect of prolonged adaptation to training and fat- or carbohydrate-rich diet on body composition and insulin resistance....
Eseryel, Deniz; Schuver-van Blanken, Marian J.; Spector, J. Michael
ADAPT[IT] (Advanced Design Approach for Personalized Training-Interactive Tools is a European project coordinated by the Dutch National Aerospace Laboratory. The aim of ADAPT[IT] is to create and validate an effective training design methodology, based on cognitive science and leading to the integration of advanced technologies, so that the…
El-Deen, M. M. G. Naser
Significant progress has been made on maximising passive solar heating loads through the careful selection of glazing, orientation and internal mass within building spaces. Control of space heating in buildings of this type has become a complex problem. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set up and commissioning procedures. This work concerns the development and testing of an adap...
Wrangham, Richard W.; Carmody, Rachel Naomi
Charles Darwin attributed human evolutionary success to three traits. Our social habits and anatomy were important, he said, but the critical feature was our intelligence, because it led to so much else, including such traits as language, weapons, tools, boats, and the control of fire. Among these, he opined, the control of fire was “probably the greatest ever [discovery] made by man, excepting language.” Despite this early suggestion that the control of fire was even more important than tool...
Belik, Vitaly; Hövel, Philipp
We consider recurrent contagious processes on a time-varying network. As a control procedure to mitigate the epidemic, we propose an adaptive rewiring mechanism for temporary isolation of infected nodes upon their detection. As a case study, we investigate the network of pig trade in Germany. Based on extensive numerical simulations for a wide range of parameters, we demonstrate that the adaptation mechanism leads to a significant extension of the parameter range, for which most of the index nodes (origins of the epidemic) lead to vanishing epidemics. We find that diseases with detection times around a week and infectious periods up to 3 months can be effectively controlled. Furthermore the performance of adaptation is very heterogeneous with respect to the index node. We identify index nodes that are most responsive to the adaptation strategy and quantify the success of the proposed adaptation scheme in dependence on the infectious period and detection times.
Alejandro Carrasco Elizalde; Peter Goldsmith
The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the cont...
Clark, Frankie J.
Approved for public release; distribution is unlimited. The Adaptive Architectures for Command and Control (A2C2) project is an ongoing research effort sponsored by the Office of Naval Research to explore adaptation in joint command and control. The objective of the project's eighth experiment is to study the adjustments that organizations make when they are confronted with a scenario for which their organizational is ill-suited. To accomplish this, teams will each be in one of two fundame...
Hansen, Poul Erik; Conrad, Finn
Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....
Full Text Available The aim of the present study was to examine the influence of intermittent hypoxia at rest and in combination with long-term high-intensity swimming exercise on lipid peroxidation and antioxidant defense system adaptation in skeletal muscles differing in fiber type composition. High-intensity chronic exercise was performed as swimming training with load that corresponded to ~ 75 % VO2max (30 min·day-1, 5 days·wk-1, for 4 wk. Intermittent hypoxic training (IHT consisted of repeated episodes of hypoxia (12%O2, 15 min, interrupted by equal periods of recovery (5 sessions/day, for 2 wk. Sessions of IHT were used during the first two weeks and during the last two weeks of chronic exercise. Oxidative (red gastrocnemius and soleus, mix and glycolytic (white gastrocnemius muscles were sampled. Our results indicated that high-intensity swim training in combination with sessions of IHT induced more profound antioxidative adaptations in skeletal muscles than the exercise training only. This adaptation has muscle fiber type specificity and is reflected in significantly elevated superoxide dismutase and catalase activities in highly oxidative muscle only. Training adaptation of GSH system (reduced glutathione content, activities of glutathione reductase, glutathione peroxidase, NADPH-supplying enzyme glucose-6-phosphate dehydrogenase occurred both in slow- and fast-twitch muscles. However, this process was more effective in oxidative muscles. IHT attenuated the increase in TBARS content induced by high-intensity swimming training. The test on exercise tolerance demonstrated a significant elevation of the swimming time to exhaustion after IHT at rest and after IHT in conjunction with high-intensity exercise in comparison with untrained and chronically exercised rats. These results confirmed that sessions of IHT might improve exercise tolerance and increase maximal work capacity
Full Text Available Biofeedback therapy is a well-known and effective therapeutic treatment for constipation. A previous study suggested that adaptive biofeedback (ABF training was more effective than traditional (fixed training parameters biofeedback training. The aim of this study was to verify the effectiveness of ABF in relieving constipation-related symptoms. We noticed that in traditional biofeedback training, a patient usually receives the training twice per week. The long training sessions usually led to poor compliance. This study proposes an intensive biofeedback therapy and compares intensive therapy with nonintensive therapy in patients with constipation-related symptoms. Methods. 63 patients with constipation-related symptoms were treated with ABF between 2012 and 2013. These patients were further divided into the intensive therapy and nonintensive therapy groups. Results. A total of 63 patients were enrolled in the study, including 24 in the nonintensive therapy group and 39 in the intensive therapy group. 100% (N=21 of constipation patients achieved the primary efficacy endpoint (≥3 bowel movements/week. There was significant improvement in constipation-related symptoms after adaptive biofeedback. The intensive biofeedback therapy did not show better performance compared to nonintensive biofeedback therapy. Conclusions. This investigation provides support for the efficacy of biofeedback for constipation-related symptoms. The efficacy of intensive therapy is similar to nonintensive therapy.
Linossier, M T; Dormois, D; Perier, C; Frey, J; Geyssant, A; Denis, C
The effect of sprint training and detraining on supramaximal performances was studied in relation to muscle enzyme adaptations in eight students trained four times a week for 9 weeks on a cycle ergometer. The subjects were tested for peak oxygen uptake (VO2peak), maximal aerobic power (MAP) and maximal short-term power output (Wmax) before and after training and after 7 weeks of detraining. During these periods, biopsies were taken from vastus lateralis muscle for the determination of creatine kinase (CK), adenylate kinase (AK), glycogen phosphorylase (PHOS), hexokinase (HK), phosphofructokinase (PFK), lactate dehydrogenase (LDH) and its isozymes, 3-hydroxy-acyl-CoA dehydrogenase (HAD) and citrate synthase (CS) activities. Training induced large improvements in Wmax (28%) with slight increases (3%) in VO2peak (P power output as a result of a muscle glycogenolytic and glycolytic adaptation. A long interruption in training has negligible effects on short-sprint ability and muscle anaerobic potential. On the other hand, a persistent training stimulus is required to maintain high aerobic capacity and muscle oxidative potential. This may contribute to a rapid return to competitive fitness for sprinters and power athletes.
An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.
Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik
In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.
Li Ke-Ping; Gao Zi-You; Mao Bao-Hua
In this paper, we propose a new cellular automaton (CA) model for train movement simulations under mixed traffic conditions. A kind of control strategy is employed for trains to reduce energy consumption. In the proposed CA model, the driver controls the train movements by using some updated rules. In order to obtain a good insight into the evolution behaviours of the rail traffic flow, we investigate the space-time diagram of the rail traffic flow and the trajectories of the train movements. The numerical simulation results demonstrate that the proposed CA model can well describe the dynamic behaviours of the train movements. Some complex phenomena of train movements can be reproduced, such as the train delay propagations, etc.
Mingjun ZHANG; Huaguang ZHANG
In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.
Xiao-Yuan Luo; Zhi-Hao Zhu; Xin-Ping Guan
In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of "explosion of complexity" in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globaily uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller (SMC). Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.
Thiago Santos Rosa
Full Text Available Severe obesity affects metabolism with potential to influence the lactate and glycemic response to different exercise intensities in untrained and trained rats. Here we evaluated metabolic thresholds and maximal aerobic capacity in rats with severe obesity and lean counterparts at pre- and post-training. Zucker rats (obese: n = 10, lean: n = 10 were submitted to constant treadmill bouts, to determine the maximal lactate steady state, and an incremental treadmill test, to determine the lactate threshold, glycemic threshold and maximal velocity at pre and post 8 weeks of treadmill training. Velocities of the lactate threshold and glycemic threshold agreed with the maximal lactate steady state velocity on most comparisons. The maximal lactate steady state velocity occurred at higher percentage of the maximal velocity in Zucker rats at pre-training than the percentage commonly reported and used for training prescription for other rat strains (i.e., 60% (obese = 78±9% and lean = 68±5%, P 0.05, whereas increase in maximal velocity was greater in the obese group (P <0.05 vs. lean. In conclusion, lactate threshold, glycemic threshold and maximal lactate steady state occurred at similar exercise intensity in Zucker rats at pre- and post-training. Severe obesity shifted metabolic thresholds to higher exercise intensity at pre-training, but did not attenuate submaximal and maximal aerobic training adaptations.
Rosa, Thiago S.; Simões, Herbert G.; Rogero, Marcelo M.; Moraes, Milton R.; Denadai, Benedito S.; Arida, Ricardo M.; Andrade, Marília S.; Silva, Bruno M.
Severe obesity affects metabolism with potential to influence the lactate and glycemic response to different exercise intensities in untrained and trained rats. Here we evaluated metabolic thresholds and maximal aerobic capacity in rats with severe obesity and lean counterparts at pre- and post-training. Zucker rats (obese: n = 10, lean: n = 10) were submitted to constant treadmill bouts, to determine the maximal lactate steady state, and an incremental treadmill test, to determine the lactate threshold, glycemic threshold and maximal velocity at pre and post 8 weeks of treadmill training. Velocities of the lactate threshold and glycemic threshold agreed with the maximal lactate steady state velocity on most comparisons. The maximal lactate steady state velocity occurred at higher percentage of the maximal velocity in Zucker rats at pre-training than the percentage commonly reported and used for training prescription for other rat strains (i.e., 60%) (obese = 78 ± 9% and lean = 68 ± 5%, P 0.05), whereas increase in maximal velocity was greater in the obese group (P < 0.05 vs. lean). In conclusion, lactate threshold, glycemic threshold and maximal lactate steady state occurred at similar exercise intensity in Zucker rats at pre- and post-training. Severe obesity shifted metabolic thresholds to higher exercise intensity at pre-training, but did not attenuate submaximal and maximal aerobic training adaptations. PMID:27148063
... SAFETY BOARD Positive Train Control Public Forum On Wednesday, February 27, 2013, the National Transportation Safety Board (NTSB) will convene a Forum titled, ``Positive Train Control: Is it on Track?'' The Forum will begin at 9:00 a.m. is open to all and the attendance is free (no registration required)....
Berkhoff, A.P.; Wesselink, J.M.
Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the amount
Nuclear power plant's safety is very important problem. In this very conscientious environment if operator has a little mistake, they may threaten with many people influence their safety. Therefore, operating training of control room is very important. However, the operator training is in limited space and time. Each operator must go to simulative control room do some training. If we can let each trainee having more time to do training and does not go to simulative control room. It may have some advantages for trainee. Moreover, in the traditional training ways, each operator may through the video, teaching manual or through the experienced instructor to learn the knowledge. This training way may let operator feel bored and stressful. So, in this paper aims, we hope utilizing virtual reality technology developing a game-based virtual training environment of control room. Finally, we will use presence questionnaire evaluating realism and feasibility of our virtual training environment. Expecting this initial concept of game-based virtual training environment can attract trainees having more learning motivation to do training in off-hour. (author)
Jones, K; Bishop, P; Hunter, G; Fleisig, G
The purpose of this study was to compare changes in velocity-specific adaptations in moderately resistance-trained athletes who trained with either low or high resistances. The study used tests of sport-specific skills across an intermediate- to high-velocity spectrum. Thirty NCAA Division I baseball players were randomly assigned to either a low-resistance (40-60% 1 repetition maximum [1RM]) training group or a high-resistance (70-90% 1RM) training group. Both of the training groups intended to maximallv accelerate each repetition during the concentric phase (IMCA). The 10 weeks of training consisted of 4 training sessions a week using basic core exercises. Peak force, velocity, and power were evaluated during set angle and depth jumps as well as weighted jumps using 30 and 50% 1RM. Squat 1RMs were also tested. Although no interactions for any of the jump tests were found, trends supported the hypothesis of velocity-specific training. Percentage gains suggest that the combined use of heavier training loads (70-90% 1RM) and IMCA tend to increase peak force in the lower-body leg and hip extensors. Trends also show that the combined use of lighter training loads (40-60% 1RM) and IMCA tend to increase peak power and peak velocity in the lower-body leg and hip extensors. The high-resistance group improved squats more than the low-resistance group (p IMCA to increase 1RM strength in the lower bodies of resistance-trained athletes.
Zhang, Bi; Hong, Hyokchan; Mao, Zhizhong
The Hammerstein-Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein-Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.
Yizhong WANG; Huaguang ZHANG; Jun YANG
This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.
National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...
Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang
This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of...
Full Text Available A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control system was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter
Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik;
This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures...... for towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify...
Jens G. Balchen
Full Text Available A technique for the adaptation of controller parameters in a single control loop based upon the estimation of frequency response parameters has been presented in an earlier paper. This paper contains an extension and a generalization of the first method and results in a more versatile solution which is applicable to a wider range of process characteristics. The application of this adaptive control technique is illustrated by a laboratory refrigeration cycle in which the evaporator pressure controls the speed of the compressor.
SZWABE Andrzej; SCHORR Andreas; HAUCK Franz J.; KASSLER Andreas J.
Dynamic adaptation of multimedia content is seen as an important feature of next generation networks and pervasive systems enabling terminals and applications to adapt to changes in e.g. context, access network, and available Quality-of-Service(QoS) due to mobility of users, devices or sessions. We present the architecture of a multimedia stream adaptation service which enables communication between terminals having heterogeneous hardware and software capabilities and served by heterogeneous networks. The service runs on special content adaptation nodes which can be placed at any location within the network. The flexible structure of our architecture allows using a variety of different adaptation engines. A generic transcoding engine is used to change the codec of streams. An MPEG-21 Digital Item Adaptation (DIA) based transformation engine allows adjusting the data rate of scalable media streams. An intelligent decision-taking engine implements adaptive flow control which takes into account current network QoS parameters and congestion information. Measurements demonstrate the quality gains achieved through adaptive congestion control mechanisms under conditions typical for a heterogeneous network.
Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John
This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.
McClung, James P.; Lee M. Margolis; Williams, Kelly W; Young, Andrew J.; J. Philip Karl; Rood, Jennifer C.; Cable, Sonya J; Pasiakos, Stefan M.
Fat-free mass (FFM) adaptations to physical training may differ between sexes based on disparities in fitness level, dietary intake, and levels of plasma amino acids (AA). This investigation aimed to determine FFM and plasma AA responses to military training, examine whether adaptations differ between male and female recruits, and explore potential associations between FFM and AA responses to training. Body composition and plasma AA levels were assessed in US Army recruits (n = 209, 118 males...
Full Text Available Lynda Norton,1 Kevin Norton,2 Nicole Lewis21School of Medicine, Flinders University, Adelaide, Australia; 2School of Health Science, University of South Australia, Adelaide, AustraliaPurpose: Numerous studies have measured changes in fasting blood glucose (FBG levels in response to physical activity (PA interventions. While studies involving clinical populations such as type 2 diabetics typically report significant reductions, most others report no change in FBG. This study investigated changes in FBG in apparently healthy adults following a PA intervention.Methods: We measured fingertip samples for FBG pre and post a 40-day PA program in 575 insufficiently active adults. The PA goal was at least 30 minutes of moderate exercise daily, and there was 73% compliance.Results: A PA questionnaire showed the average level of activity was 69 ± 46 min/wk preintervention, and this increased to 635 ± 458 min/wk postintervention. When the change in FBG was regressed against baseline FBG levels, there was a significant negative relationship (y = 2.623 – 0.471 × x; r = 0.472; P < 0.0001. The regression line showed, on average, subjects with low pre-study glucose levels had increased FBG while those with high levels had reductions in FBG.Conclusion: It appears that the body's response to PA training is to upregulate glucose control, which is reflected in tighter FBG levels around a physiological set point (5.6 mmol/L, in the present study. Regulation of blood glucose is a complex neuroendocrine process with numerous organs involved, but it was not possible in the present study to determine which of these regulatory steps are involved in exercise-induced changes of FBG.Keywords: physical activity, glucagon, insulin sensitivity
Wilms, Inge Linda
-based training systems, that secures a reasonable and individualized progression in the level of difficulty presented to the patient during training. This study investigates the possibility of using the actor/critic method from the discipline of reinforcement learning, to control the level of difficulty during...
LIU Yu-sheng; CHEN Jiang; LI Xing-yuan
Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.
Helge, Jørn Wulff
It is well known that adaptation to a fat-rich carbohydrate-poor diet results in lower resting muscle glycogen content and a higher rate of fat oxidation during exercise when compared with a carbohydrate-rich diet. The net effect of such an adaptation could potentially be a sparing of muscle...... glycogen, and because muscle glycogen storage is coupled to endurance performance, it is possible that adaptation to a high-fat diet potentially could enhance endurance performance. Therefore, the first issue in this review is to critically evaluate the available evidence for a potential endurance...... performance enhancement after long-term fat-rich diet adaptation. Attainment of optimal performance is among other factors dependent also on the quality and quantity of the training performed. When exercise intensity is increased, there is an increased need for carbohydrates. On the other hand, consumption...
Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.
Merrill, W.; Leininger, G.
The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.
In the book (Adaptive Identification,Prediction and Control-Multi Level Recursive Approach), the concept of dynamical linearization of nonlinear systems has been presented.This dynamical linearization is formal only,not a real linearization.From the linearization procedure,we can find a new approach of system identification,which is on-line real-time modeling and real-time feedback control correction.The modeling and real-time feedback control have been integrated in the identification approach,with the parameter adaptation model being abandoned.The structure adaptation of control systems has been achieved,which avoids the complex modeling steps.The objective of this paper is to introduce the approach of integrated modeling and control.
YAO Jianyong; JIAO Zongxia; YAO Bin; SHANG Yaoxing; DONG Wenbin
This paper deals with the high performance force control of hydraulic load samulator.Many prevtous works for hydraultc force control are based on their linearization equations,but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements.In this paper,a nonlinear system model is derived and linear parameterization is made for adaptive control.Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator.The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws,which can compensate for the system nonlinearities and uncertain parameters.Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities.The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities,the scheme also achieves asymptotic tracking performance.Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.
Lefevre, Brian D.
For the purpose of maintaining dynamic stability and improving guidance command tracking performance under off-nominal flight conditions, a hybrid adaptive control scheme is selected and modified for use as a launch vehicle flight controller. This architecture merges a model reference adaptive approach, which utilizes both direct and indirect adaptive elements, with a classical dynamic inversion controller. This structure is chosen for a number of reasons: the properties of the reference model can be easily adjusted to tune the desired handling qualities of the spacecraft, the indirect adaptive element (which consists of an online parameter identification algorithm) continually refines the estimates of the evolving characteristic parameters utilized in the dynamic inversion, and the direct adaptive element (which consists of a neural network) augments the linear feedback signal to compensate for any nonlinearities in the vehicle dynamics. The combination of these elements enables the control system to retain the nonlinear capabilities of an adaptive network while relying heavily on the linear portion of the feedback signal to dictate the dynamic response under most operating conditions. To begin the analysis, the ascent dynamics of a launch vehicle with a single 1st stage rocket motor (typical of the Ares 1 spacecraft) are characterized. The dynamics are then linearized with assumptions that are appropriate for a launch vehicle, so that the resulting equations may be inverted by the flight controller in order to compute the control signals necessary to generate the desired response from the vehicle. Next, the development of the hybrid adaptive launch vehicle ascent flight control architecture is discussed in detail. Alterations of the generic hybrid adaptive control architecture include the incorporation of a command conversion operation which transforms guidance input from quaternion form (as provided by NASA) to the body-fixed angular rate commands needed by the
Full Text Available Unmanned Aerial Vehicle (UAV is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine (SVM is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system.
De Croon, G.C.H.E.; Postma, E.O.; Van den Herik, H.J.
We propose a novel gaze-control model for detecting objects in images. The model, named act-detect, uses the information from local image samples in order to shift its gaze towards object locations. The model constitutes two main contributions. The first contribution is that the model’s setup makes
El-Nagar, Ahmad M
In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. PMID:27342993
Full Text Available Purpose: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters.Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system, used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS consisting of two neural identificators of the process dynamics and primary regulator.Findings: The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.Research limitations/implications: The proposed architecture for on-line determining of optimal cutting conditions is applied to ball-end milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry.Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.
Luo, Wan; Billings, Steve A.; Fung, Chi F.
A new recursive supervised training algorithm is derived for the radial basis neural network architecture. The new algorithm combines the procedures of on-line candidate regressor selection with the conventional Givens QR based recursive parameter estimator to provide efficient adaptive supervised network training. A new concise on-line correlation based performance monitoring scheme is also introduced as an auxiliary device to detect structural changes in temporal data processing applications. Practical and simulated examples are included to demonstrate the effectiveness of the new procedures. Copyright 1996 Elsevier Science Ltd.
The aim of the present study was to examine the influence of intermittent hypoxia at rest and in combination with long-term high-intensity swimming exercise on lipid peroxidation and antioxidant defense system adaptation in skeletal muscles differing in fiber type composition. High-intensity chronic exercise was performed as swimming training with load that corresponded to ~ 75 % VO2max (30 min·day-1, 5 days·wk-1, for 4 wk). Intermittent hypoxic training (IHT) consisted of repeated episodes o...
Rasmussen, Henrik; Larsen, Lars F. S.
are capable of adapting to variety of systems. This paper proposes a novel method for superheat and capacity control of refrigeration systems; namely by controlling the superheat by the compressor speed and capacity by the refrigerant flow. A new low order nonlinear model of the evaporator is developed...... and used in a backstepping design of a nonlinear adaptive controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results show the performance of the system for a wide range of operating points. The method is compared to a conventional method based...
Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.
Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.
Saito, Asaki; Konishi, Keiji
We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398
Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.
Alejandro Carrasco Elizalde
Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.
Dynamic model and control strategy of parallel mechanism have always been a problem in robotics research. In this paper,different dynamics formulation methods are discussed first, A model of redundant driven parallel mechanism with a planar parallel manipulator is then constructed as an example. A nonlinear adaptive control method is introduced. Matrix pseudo-inversion is used to get a desired actuator torque from a desired end-effector coordinate while the feedback torque is directly calculated in the actuator space. This treatment avoids forward kinematics computation that is very difficult in a parallel mechanism. Experiments with PID together with the descibed adaptive control strategy were carried out for a planar parallel mechanism. The results show that the proposed adaptive controller outperforms conventional PID methods in tracking desired input at a high speed,
Christensen, Anders; Ravn, Ole
SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows a t...
Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede
sensitivity of the most popular harmonic controllers for grid-interfaced converters. The frequency adaptability of these harmonic controllers is evaluated in the presence of a variable grid frequency within a specified reasonable range, e.g., +-1% of the nominal grid frequency (50 Hz). Solutions...
Bagchi, Arunabha; Chen, Han-Fu
We study linear-quadratic adaptive tracking problems for a special class of stochastic systems expressed in the state-space form. This is a long-standing problem in the control of aircraft flying through atmospheric turbulence. Using an ELS-based algorithm and introducing dither in the control law w
Battistelli, Giorgio; Hespanha, João; Mosca, Edoardo; Tesi, Pietro
In recent years, unfalsified adaptive switching supervisory control (UASSC) has emerged as an effective technique for tackling the problem of controlling uncertain plants only on the basis of the plant I/O data. The aim of this paper is to construct a novel switching logic, which, when combined with
Niet, de, A.; Vrugt, van de, Noëlle Maria; Korving, Hans; Boucherie, Richard J.; Savic, D.A.; Kapelan, Z.; Butler, D.
In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is...
Fransson, Per-Anders; Hafström, Anna; Karlberg, Mikael; Magnusson, Måns; Tjäder, Annika; Johansson, Rolf
he objective for this study was to investigate whether the adaptation of postural control was similar during galvanic vestibular stimulation and during vibratory proprioceptivestimulation of the calf muscles. Healthy subjects were tested during erect stance with eyes open or closed. An analysis method designed to consider the adaptive adjustments was used to evaluate the motion dynamics and the evoked changes of posture and stimulation response.Galvanic vestibular stimulation induced primaril...
Clayton, Dale H.; Moyer, Brett R; Bush, Sarah E.; Jones, Tony G; Gardiner, David W; Rhodes, Barry B; Goller, Franz
The beaks of Darwin's finches and other birds are among the best known examples of adaptive evolution. Beak morphology is usually interpreted in relation to its critical role in feeding. However, the beak also plays an important role in preening, which is the first line of defence against harmful ectoparasites such as feather lice, fleas, bugs, flies, ticks and feather mites. Here, we show a feature of the beak specifically adapted for ectoparasite control. Experimental trimming of the tiny (...
Landau Ioan Doré
The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and time-varying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented.
Chen Yimei; Han Zhengzhi; Tang Houjun
The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.
Lucas eSpierer; Camille eChavan; Aurelie Lynn Manuel
Deficits in inhibitory control, the ability to suppress ongoing or planned motor or cognitive processes, contribute to many psychiatric and neurological disorders. The rehabilitation of inhibition-related disorders may therefore benefit from neuroplasticity-based training protocols aiming at normalizing inhibitory control proficiency and the underlying brain networks. Current literature on training-induced behavioral and brain plasticity in inhibitory control suggests that improvements may fo...
Baer-Riedhart, Jennifer L.; Landy, Robert J.
The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.
Xia, Feng; Peng, Chen; Sun, Youxian; Dong, Jinxiang
There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results sh...
Cherrett, Tom; Gates, James C.; John, Pearl; Holdaway-Salmon, Laura; Price, Joseph; Wills, Gary B; Dror, Itiel E.
The cost of health and safety failures to UK industry is currently estimated at £6.5 billion per annum. Better health and safety education (particularly re-training) across all skill levels is seen as an integral part of any solution. Traditional lecture-based courses often fail to re-create the dynamic realities of managing health and safety on-site or in-the-lab, and therefore do not sufficiently engage the students in deeper learning (which results in remembering and using what was learned...
National Aeronautics and Space Administration — We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller...
Hansen, Jens Peter; Ostergaard, Birte; Nordentoft, Merete;
Cognitive adaptation training (CAT) has been tested as a psychosocial treatment, showing promising results. To date there are no reported tests of CAT treatment outside the United States. Thus, we decided to adjust CAT treatment and apply it to an Integrated Treatment setting in Denmark. In this ......Cognitive adaptation training (CAT) has been tested as a psychosocial treatment, showing promising results. To date there are no reported tests of CAT treatment outside the United States. Thus, we decided to adjust CAT treatment and apply it to an Integrated Treatment setting in Denmark...... and quality of life were assessed using instruments validated in a Danish context. It was judged that, after some adjustments to fit the Danish assertive community treatment, CAT treatment was feasible in a Danish setting....
Hounsgaard, Lise; Hansen, J. P.; Østergaard, B.;
Cognitive adaptation training (CAT) has been tested as a psychosocial treatment, showing promising results. To date there are no reported tests of CAT treatment outside the United States. Thus, we decided to adjust CAT treatment and apply it to an Integrated Treatment setting in Denmark. In this ......Cognitive adaptation training (CAT) has been tested as a psychosocial treatment, showing promising results. To date there are no reported tests of CAT treatment outside the United States. Thus, we decided to adjust CAT treatment and apply it to an Integrated Treatment setting in Denmark...... and quality of life were assessed using instruments validated in a Danish context. It was judged that, after some adjustments to fit the Danish assertive community treatment, CAT treatment was feasible in a Danish setting....
Helge, Jørn Wulff; Watt, Peter W; Richter, Erik A;
We tested the hypothesis that a shift to carbohydrate diet after prolonged adaptation to fat diet would lead to decreased glucose uptake and impaired muscle glycogen breakdown during exercise compared with ingestion of a carbohydrate diet all along. We studied 13 untrained men; 7 consumed a high......-fat (Fat-CHO; 62% fat, 21% carbohydrate) and 6 a high-carbohydrate diet (CHO; 20% fat, 65% carbohydrate) for 7 wk, and thereafter both groups consumed the carbohydrate diet for an eighth week. Training was performed throughout. After 8 wk, during 60 min of exercise (71 +/- 1% pretraining maximal oxygen...... +/- 59 vs. 688 +/- 43 mmol/kg dry wt) in Fat-CHO than in CHO. In conclusion, shift to carbohydrate diet after prolonged adaptation to fat diet and training causes increased resting muscle glycogen levels but impaired leg glucose uptake and similar muscle glycogen breakdown, despite higher resting levels...
Lund, Henrik Hautop; Jessen, Jari Due
, agility, endurance, and sensor-motoric reaction. A population of 12 elderly (average age: 79) with balancing problems (DGI average score: 18.7) was randomly assigned to control group or tiles training group, and tested before and after intervention. The tiles training group had statistical significant...... increase in balancing performance (DGI score: 21.3) after short-term playful training with the modular interactive tiles, whereas the control group remained with a score indicating balancing problems and risk of falling (DGI score: 16.6). The small pilot randomized controlled trial suggests...
Zhang, Yanjun; Tao, Gang; Chen, Mou
This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.
Li Chunguang; Liao Xiaofeng; Wu Zhongfu; Yu Juebang
In this paper, the layer-by-layer optimizing algorithm for training multilayer neural network is extended for the case of a multilayer neural network whose inputs, weights, and activation functions are all complex. The updating of the weights of each layer in the network is based on the recursive least squares method. The performance of the proposed algorithm is demonstrated with application in adaptive complex communication channel equalization.
Assaf, Tareq; Rossiter, Jonathan M.; Porrill, John
Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. PMID:27655667
... of processor-based train control systems. See 70 FR 11,052 (Mar. 7, 2005) (codified at 49 CFR part... passenger trains operating at greater than 59 miles per hour under Sec. 236.0(c)(2). See 75 FR 2598 at 2607...); Louisville Jeffersonville Bridge Co. v. United States, 249 U.S. 543 (1919); see also 66 FR 4104, 4148 (Jan...
Pronunciation training based on speech production techniques illustrating tongue movements is gaining popularity. However, there is not sufficient evidence that learners can imitate some tongue animation. In this paper, we argue that although controlling tongue movement related to speech is not such an easy task, training with visual feedback…
Full Text Available Purpose. To evaluate training induced metabolic changes noninvasively with magnetic resonance spectroscopy (-MRS for measuring muscle fibre type adaptation. Methods. Eleven volunteers underwent a 24-week training, consisting of speed-strength, endurance, and detraining (each 8 weeks. Prior to and following each training period, needle biopsies and -MRS of the resting gastrocnemius muscle were performed. Fibre type distribution was analyzed histologically and tested for correlation with the ratios of high energy phosphates ([PCr]/, [PCr]/[βATP] and [PCr + ]/[βATP]. The correlation between the changes of the -MRS parameters during training and the resulting changes in fibre composition were also analysed. Results. We observed an increased type-II-fibre proportion after speed-strength and detraining. After endurance training the percentage of fast-twitch fibres was reduced. The progression of the [PCr]/-ratio was similar to that of the fast-twitch fibres during the training. We found a correlation between the type-II-fibre proportion and [PCr]/ (, or [PCr]/[βATP] (, ; the correlations between its changes (delta and the fibre-shift were significant as well (delta[PCr]/ , delta[PCr]/[βATP] , . Conclusion. Shifts in fibre type composition and high energy phosphate metabolite content covary in human gastrocnemius muscle. Therefore -MRS might be a feasible method for noninvasive monitoring of exercise-induced fibre type transformation.
Rhea Matthew R.
Full Text Available Purpose. The purpose of this study was to examine the influence of training at different ranges of motion during the squat exercise on joint-angle specific strength adaptations. Methods. Twenty eight men were randomly assigned to one of three training groups, differing only in the depth of squats (quarter squat, half squat, and full squat performed in 16-week training intervention. Strength measures were conducted in the back squat pre-, mid-, and post-training at all three depths. Vertical jump and 40-yard sprint time were also measured. Results. Individuals in the quarter and full squat training groups improved significantly more at the specific depth at which they trained when compared to the other two groups (p < 0.05. Jump height and sprint speed improved in all groups (p < 0.05; however, the quarter squat had the greatest transfer to both outcomes. Conclusions. Consistently including quarter squats in workouts aimed at maximizing speed and jumping power can result in greater improvements.
Full Text Available Purpose: studying of the main parameters of morphofunctional condition of the left ventricular cavity of heart of sportsmen in the conditions of the training and competitive activity. Material & Methods: three groups of children (n=30 of 7–9, 10–12, 13–14 years old, who begin to train in sports with the manifestation of endurance and high-speed and power qualities, the qualified sportsmen at the age of 15–16 years old, who are engaged in run on 400 m with barriers, and karatekas (n=15+n=15, not engaged children of the same aged groups (n=40. The following methods of the research were applied: analysis of special literature, pedagogical supervisions, pedagogical experiment, echocardiological methods of the research. Results: the considerable connection of types of heart of young sportsmen with indicators of exercise stress of various orientations is established. Sportsmen with the optimum vegeto-rhythmic indicators have the essential advantages in adaptation morphofunctional displacements in heart and warm productivity at sportsmen with satisfactory vegetative-rhythmic indicators. Conclusions: adaptation morphofunctional displacements in activity of the cardio-respiratory system are closely connected with the prevailing orientation of the training process and can be used as the objective test of adaptation to the special loadings in sport.
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
SONG Yimin; LI Jianxin; WANG Shiyu; LIU Jianping
An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted.The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors.A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator.The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced.The neuro-identifier and the neurocontroller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC.By adjusting the neuro-identifier and the neuro-controller alternatively,the manipulator was controlled on line for achieving the desired dynamic performance.Finally,a planar 3R redundant manipulator with one smart link was utilized as an illustrative example.The simulation results proved the validity of the control strategy.
Sundararajan, N.; Goglia, G. L.
The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.
Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.
LIU Yusheng; LI Xingyuan
The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.
It is well known that the transient behaviors of the traditional adaptive control may be very poor in general,and that the adaptive control designed based in switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances.In this paper,we shall prove that for a typical class of linear systems disturbed by random noises,the multiple model based least-equares(LS)adaptive switching control is statble and convergent and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators.Moreover,the mixed case combining adative models with fixed models is also considered.
Boutalis, Yiannis; Kottas, Theodore; Christodoulou, Manolis A
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering s...
Full Text Available This paper proposes an adaptive Nonlinear Model Predictive Controller (NMPC for hybrid position/velocity control of robot manipulators. Robot dynamics have generally uncertainties, including parameters variations, unknown nonlinearities of the robot, payload variations, and torque disturbances form the environment. The cost function of the NMPC is defined in such a way that by adjusting its weighting parameters, the end-effector of the robot tracks a predefined geometry path in Cartesian space with a constant velocity. Moreover, to eliminate the uncertainties, a neural network with Levenberg-Marquardt training algorithm is used to estimate adaptively the model of the robot. The closed-loop stability is demonstrated using Lyapunov theory. The validity of the proposed control method is shown by simulation results on a 3-DOF robot manipulator actuated by DC servomotors.
Li Chuntao; Tan Yonghong
An adaptive control scheme is developed for a class of single-input nonlinear systems preceded by unknown hysteresis, which is a non-differentiable and multi-value mapping nonlinearity. The controller based on the three-layer neural network (NN), whose weights are derived from Lyapunov stability analysis, guarantees closed-loop semiglobal stability and convergence of the tracking errors to a small residual set. An example is used to confirm the effectiveness of the proposed control scheme.
Helge, Jørn Wulff
the review will address the available studies on low-intensity training performed separately with arm or legs or as whole-body training to evaluate if this leads to different adaptations in arm and leg muscle resulting in different substrate utilization patterns during separate arm or leg exercise...... partitioning between endogenous and exogenous substrate during arm and leg exercise will be debated. Moreover the review will probe if differences between arm and leg muscle are merely a result of different training status rather than a qualitative difference in limb substrate regulation. Along this line......This review will focus on current data where substrate metabolism in arm and leg muscle is investigated and discuss the presence of higher carbohydrate oxidation and lactate release observed during arm compared with leg exercise. Furthermore, a basis for a possible difference in substrate...
Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin
Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.
Liu, Zhi; Zhang, Yun; Chen, C. L. Philip
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.
Rabinowitz, Matthew (Inventor)
Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.
Spike generation in neurons produces a temporal point process, whose statistics is governed by intrinsic phenomena and the external incoming inputs to be coded. In particular, spike-evoked adaptation currents support a slow temporal process that conditions spiking probability at the present time according to past activity. In this work, we study the statistics of interspike interval correlations arising in such non-renewal spike trains, for a neuron model that reproduces different spike modes in a small adaptation scenario. We found that correlations are stronger as the neuron fires at a particular firing rate, which is defined by the adaptation process. When set in a subthreshold regime, the neuron may sustain this particular firing rate, and thus induce correlations, by noise. Given that, in this regime, interspike intervals are negatively correlated at any lag, this effect surprisingly implies a reduction in the variability of the spike count statistics at a finite noise intensity.
Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.
LIU Min; XU Shijie; HAN Chao
Although the simple adaptive control (SAC) is widely studied both in theory and application in flexible space structure control and other control problems,it is restricted by the almost strictly positive real (ASPR) conditions.In most practical control problems,the ASPR conditions are not satisfied.Therefore,based on the SAC theory,this paper proposes a backstepping simple adaptive control algorithm which suits the system with arbitrary relative degree with no need of parallel feedforward compensator.The proposed control algorithm consists of decomposition of the arbitrary relative degree system into a known subsystem and an unknown ASPR subsystem which are eonneeted in cascade,design of constant outpul feedback controller for the known subsystem,and implementation of backstepping method and SAC of the unknown ASPR subsystem.Inheriting the characteristics of the SAC,this method can be adaptive online for the parameter uncertainties.Then,the application of the proposed controller to large flexible space structure with collocated sensors and actuators is studied,and the simulation results validate the proposed controller.It is a new strategy to apply the classical SAC to high relative degree plants.
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model of ...... current controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....
Rasmussen, Henrik; Vadstrup, P.; Børsting, H.
It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model of ...... controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....
This work investigates adaptive control of a large class of uncertain me-delay chaotic systems (UTCSs) with unknown general perturbation terms bounded by a polynomial ( unknown gains). Associated with the different cases of known and unknown system matrices, two corresponding adaptive controllers are proposed to stabilize unstable fixed points of the systems by means of Lyapunov stability theory and linear matrix inequalities (LMI) which can be solved easily by convex optimization algorithms. Two examples are used for examining the effectiveness of the proposed methods.
Hussain, Zakaria; Bin Zaidan, Martha Arbayani; M.O. Tokhi; Jailani, Rozita
This paper describes the development of an adaptive control mechanism for FES-assisted indoor rowing exercise (FES-rowing). The FES-rowing is intro-duced as a total body exercise for rehabilitation of function of lower body through the application of functional elec-trical stimulation (FES). A model of the rowing ergometer with humanoid is developed using the visual Nastran soft-ware environment (vN4D). A fuzzy logic control (FLC) scheme is designed in Matlab/Simulink and adapted online by pr...
Lira, Vitor A; Okutsu, Mitsuharu; Zhang, Mei; Greene, Nicholas P; Laker, Rhianna C; Breen, David S; Hoehn, Kyle L; Yan, Zhen
Pathological and physiological stimuli, including acute exercise, activate autophagy; however, it is unknown whether exercise training alters basal levels of autophagy and whether autophagy is required for skeletal muscle adaptation to training. We observed greater autophagy flux (i.e., a combination of increased LC3-II/LC3-I ratio and LC3-II levels and reduced p62 protein content indicating a higher rate of initiation and resolution of autophagic events), autophagy protein expression (i.e., Atg6/Beclin1, Atg7, and Atg8/LC3) and mitophagy protein Bnip3 expression in tonic, oxidative muscle compared to muscles of either mixed fiber types or of predominant glycolytic fibers in mice. Long-term voluntary running (4 wk) resulted in increased basal autophagy flux and expression of autophagy proteins and Bnip3 in parallel to mitochondrial biogenesis in plantaris muscle with mixed fiber types. Conversely, exercise training promoted autophagy protein expression with no significant increases of autophagy flux and mitochondrial biogenesis in the oxidative soleus muscle. We also observed increased basal autophagy flux and Bnip3 content without increases in autophagy protein expression in the plantaris muscle of sedentary muscle-specific Pgc-1α transgenic mice, a genetic model of augmented mitochondrial biogenesis. These findings reveal that endurance exercise training-induced increases in basal autophagy, including mitophagy, only take place if an enhanced oxidative phenotype is achieved. However, autophagy protein expression is mainly dictated by contractile activity independently of enhancements in oxidative phenotype. Exercise-trained mice heterozygous for the critical autophagy protein Atg6 showed attenuated increases of basal autophagy flux, mitochondrial content, and angiogenesis in skeletal muscle, along with impaired improvement of endurance capacity. These results demonstrate that increased basal autophagy is required for endurance exercise training-induced skeletal
Full Text Available The paper deals with new training technologies development based on approach to distance learning website, implemented in the laboratory of a Traffic Engineering study branch at Faculty of Transport. The discussed computing interface allows students complete knowledge of traffic controllers’ architecture and machine language programming fundamentals. These training facilities are available at home; at their remote terminal. The training resources consist of electronic / computer based training; guidebooks and software units. The laboratory provides the students with an interface entering into simulation packages and programming interfaces, supporting the web training facilities. The courseware complexity selection is one of the most difficult factors in intelligent training unit’s development. The dynamically configured application provides the user with his individually set structure of the training resources. The trainee controls the application structure and complexity, from the time he started. For simplifying the training process and studying activities, several unifications were provided. The introduced ideas need various standardisations, simplifying the e-learning units’ development and application control processes , . Further training facilities development concerns virtual laboratory environment organisation in laboratories of Transport Faculty.
Yang Chunhui; Liu Junxian; Chen Honghui; Luo Xueshan
Adaptive optimization is one of the means that agile organization of command and control resource (AOC2R) adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net (CPN) model of AOC2R and then searches for the result by ant colony optimization (ACO) algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.
The performance of plant maintenance-related tasks assigned to instrumentation and control (I ampersand C) technicians can be broken down into physical skills required to do the task; resident knowledge of how to do the task; effect of maintenance on plant operating conditions; interactions with other plant organizations such as operations, radiation protection, and quality control; and knowledge of consequences of miss-action. A technician who has learned about the task in formal classroom presentations has not had the advantage of integrating that knowledge with the requisite physical and communication skills; hence, the first time these distinct and vital parts of the task equation are put together is on the job, during initial task performance. On-the-job training provides for the integration of skills and knowledge; however, this form of training is limited by plant conditions, availability of supporting players, and training experience levels of the personnel conducting the exercise. For licensed operations personnel, most nuclear utilities use formal classroom and a full-scope control room simulator to achieve the integration of skills and knowledge in a controlled training environment. TU Electric has taken that same approach into maintenance areas by including identical plant equipment in a laboratory setting for the large portion of training received by maintenance personnel at its Comanche Peak steam electric station. The policy of determining training needs and defining the scope of training by using the systematic approach to training has been highly effective and provided training at a reasonable cost (approximately $18.00/student contact hour)
Full Text Available This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.
Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang
This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.
The variation of joint groove size during tungsten inert gas (TIG) welding will result in the non-uniform fill of deposited metal. To solve this problem, an adaptive fill control system was developed based on laser vision sensing. The system hardware consists of a modular development kit (MDK) as the real-time image capturing system, a computer as the controller, a D/A conversion card as the interface of controlled variable output, and a DC TIG welding system as the controlled device. The system software is developed and the developed feature extraction algorithm and control strategy are of good accuracy and robustness. Experimental results show that the system can implement adaptive fill of melting metal with high stability, reliability and accuracy. The groove is filled well and the quality of the weld formation satisfies the relevant industry criteria.
This paper deals with nonholonomic systems in chained form with unknown covariance stochastic disturbances. The objective is to design the almost global adaptive asymptotical controllers in probability u0 and u1 for the systems by using discontinuous control. A switching control law u0 is designed to almost globally asymptotically stabilize the state x0 in both the singular x0 (t0)=0 case and the non-singular x0 (t0)≠0 case. Then the state scaling technique is introduced for the discontinuous feedback into the (x1, x2, …, xn)-subsystem. Thereby, by using backstepping technique the global adaptive asymptotical control law u1 has been presented for (x1, x2, …, xn) -subsystem for both different u0 in non-singular x0 (t0)≠0 case and the singular case x0 (t0)=0. The control algorithm validity is proved by simulation.
A neuromorphic continuous-time state space pole assignment adaptive controller is proposed, which is particularly appropriate for controlling a large-scale time-variant state-space model due to the parallely distributed nature of neurocomputing. In our approach, Hopfield neural network is exploited to identify the parameters of a continuous-time state-space model, and a dedicated recurrent neural network is designed to compute pole placement feedback control law in real time. Thus the identification and the control computation are incorporated in the closed-loop, adaptive, real-time control system. The merit of this approach is that the neural networks converge to their solutions very quickly and simultaneously.
单剑锋; 黄忠华; 崔占忠
A scheme of adaptive control based on a recurrent neural network with a neural network compensation is presented for a class of nonlinear systems with a nonlinear prefix. The recurrent neural network is used to identify the unknown nonlinear part and compensate the difference between the real output and the identified model output. The identified model of the controlled object consists of a linear model and the neural network. The generalized minimum variance control method is used to identify pareters, which can deal with the problem of adaptive control of systems with unknown nonlinear part, which can not be controlled by traditional methods. Simulation results show that this algorithm has higher precision, faster convergent speed.
Huning, Therese; Barshi, Immanuel; Schmidt, Lacey
The Mission Operations Directorate (MOD) of the Johnson Space Center is responsible for providing continuous operations support for the International Space Station (ISS). Operations support requires flight controllers who are skilled in team performance as well as the technical operations of the ISS. Space Flight Resource Management (SFRM), a NASA adapted variant of Crew Resource Management (CRM), is the competency model used in the MOD. ISS flight controller certification has evolved to include a balanced focus on development of SFRM and technical expertise. The latest challenge the MOD faces is how to certify an ISS flight controller (operator) to a basic level of effectiveness in 1 year. SFRM training uses a two-pronged approach to expediting operator certification: 1) imbed SFRM skills training into all operator technical training and 2) use senior flight controllers as mentors. This paper focuses on how the MOD uses senior flight controllers as mentors to train SFRM skills. Methods: A mentor works with an operator throughout the training flow. Inserted into the training flow are guided-discussion sessions and on-the-job observation opportunities focusing on specific SFRM skills, including: situational leadership, conflict management, stress management, cross-cultural awareness, self care and team care while on-console, communication, workload management, and situation awareness. The mentor and operator discuss the science and art behind the skills, cultural effects on skills applications, recognition of good and bad skills applications, recognition of how skills application changes subtly in different situations, and individual goals and techniques for improving skills. Discussion: This mentoring program provides an additional means of transferring SFRM knowledge compared to traditional CRM training programs. Our future endeavors in training SFRM skills (as well as other organization s) may benefit from adding team performance skills mentoring. This paper
Ramirez-Campillo, Rodrigo; Andrade, David C; Alvarez, Cristian; Henríquez-Olguín, Carlos; Martínez, Cristian; Báez-Sanmartín, Eduardo; Silva-Urra, Juan; Burgos, Carlos; Izquierdo, Mikel
The aim of the study was to compare the effects of plyometric training using 30, 60, or 120 s of rest between sets on explosive adaptations in young soccer players. Four groups of athletes (age 10.4 ± 2.3 y; soccer experience 3.3 ± 1.5 y) were randomly formed: control (CG; n = 15), plyometric training with 30 s (G30; n = 13), 60 s (G60; n = 14), and 120 s (G120; n = 12) of rest between training sets. Before and after intervention players were measured in jump ability, 20-m sprint time, change of direction speed (CODS), and kicking performance. The training program was applied during 7 weeks, 2 sessions per week, for a total of 840 jumps. After intervention the G30, G60 and G120 groups showed a significant (p = 0.0001 - 0.04) and small to moderate effect size (ES) improvement in the countermovement jump (ES = 0.49; 0.58; 0.55), 20 cm drop jump reactive strength index (ES = 0.81; 0.89; 0.86), CODS (ES = -1.03; -0.87; -1.04), and kicking performance (ES = 0.39; 0.49; 0.43), with no differences between treatments. The study shows that 30, 60, and 120 s of rest between sets ensure similar significant and small to moderate ES improvement in jump, CODS, and kicking performance during high-intensity short-term explosive training in young male soccer players. Key pointsReplacing some soccer drills by low volume high-intensity plyometric training would be beneficial in jumping, change of direction speed, and kicking ability in young soccer players.A rest period of 30, 60 or 120 seconds between low-volume high-intensity plyometric sets would induce significant and similar explosive adaptations during a short-term training period in young soccer players.Data from this research can be helpful for soccer trainers in choosing efficient drills and characteristics of between sets recovery programs to enhance performances in young male soccer players.
Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang
A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.
Full Text Available The spatial path following control problem of autonomous underwater vehicles (AUVs is addressed in this paper. In order to realize AUVs’ spatial path following control under systemic variations and ocean current, three adaptive neural network controllers which are based on the Lyapunov stability theorem are introduced to estimate uncertain parameters of the vehicle’s model and unknown current disturbances. These controllers are designed to guarantee that all the error states in the path following system are asymptotically stable. Simulation results demonstrated that the proposed controller was effective in reducing the path following error and was robust against the disturbances caused by vehicle's uncertainty and ocean currents.
Shoureshi, Rahmat; Brackney, Larry
During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.
Vrabie, Draguna; Lewis, Frank
In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided. PMID:19362449
Full Text Available Exercise combined with whole body vibration (WBV is becoming increasingly popular, although additional effects of WBV in comparison to conventional exercises are still discussed controversially in literature. Heterogeneous findings are attributed to large differences in the training designs between WBV and "control" groups in regard to training volume, load and type. In order to separate the additional effects of WBV from the overall adaptations due to the intervention, in this study, a four-week WBV training setup was compared to a matched intervention program with identical training parameters in both training settings except for the exposure to WBV. In a repeated-measures matched-subject design, 38 participants were assigned to either the WBV group (VIB or the equivalent training group (CON. Training duration, number of sets, rest periods and task-specific instructions were matched between the groups. Balance, jump height and local static muscle endurance were assessed before and after the training period. The statistical analysis revealed significant interaction effects of group×time for balance and local static muscle endurance (p<0.05. Hence, WBV caused an additional effect on balance control (pre vs. post VIB +13%, p<0.05 and CON +6%, p = 0.33 and local static muscle endurance (pre vs. post VIB +36%, p<0.05 and CON +11%, p = 0.49. The effect on jump height remained insignificant (pre vs. post VIB +3%, p = 0.25 and CON ±0%, p = 0.82. This study provides evidence for the additional effects of WBV above conventional exercise alone. As far as balance and muscle endurance of the lower leg are concerned, a training program that includes WBV can provide supplementary benefits in young and well-trained adults compared to an equivalent program that does not include WBV.
Shin, Jongho; Jin Kim, H; Kim, Youdan
This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion error are identified off-line, which we call I-SVR (inversion SVR) and C-SVR (compensation SVR), respectively. In order to compensate for the inversion error and the unexpected uncertainty, an online adaptation algorithm for the C-SVR is proposed. Then, the stability of the overall error dynamics is analyzed by the uniformly ultimately bounded property in the nonlinear system theory. In order to validate the effectiveness of the proposed adaptive controller, numerical simulations are performed on the UAV model.
Recently, suboptimality estimates for model predictive controllers (MPC) have been derived for the case without additional stabilizing endpoint constraints or a Lyapunov function type endpoint weight. The proposed methods yield a posteriori and a priori estimates of the degree of suboptimality with respect to the infinite horizon optimal control and can be evaluated at runtime of the MPC algorithm. Our aim is to design automatic adaptation strategies of the optimization horizon in order to guarantee stability and a predefined degree of suboptimality for the closed loop solution. Here, we present a stability proof for an arbitrary adaptation scheme and state a simple shortening and prolongation strategy which can be used for adapting the optimization horizon.
Full Text Available In two recent decades, fuzzy controllers have been used in controlling different systems successfully. In this article, a new method is given for controlling of permanent magnetic DC motor connected to unbalanced load. Imbalance of load leads to machine vibrations, fluctuation of power, making exhaustion in machine shaft, and equipment depreciation. In this article neuro-fuzzy controllers are used for controlling unbalanced load. Because of non-linear nature of load and machine, machine fluctuations are different in various speeds. For making controller adaptive with machine, using an artificial neural network, the input-output coefficients are be updated in any speed. Optimized coefficients obtained by using of direct search method, and with these coefficients, artificial neural network trained with Lauvenberg-Marcoardet method. Operational results obtained from developed system, shows the efficiency of given method.
Ren, Haipeng; Fan, Juntao
With the price decreasing of the pneumatic proportional valve and the high performance micro controller, the simple structure and high tracking performance pneumatic servo system demonstrates more application potential in many fields. However, most existing control methods with high tracking performance need to know the model information and to use pressure sensor. This limits the application of the pneumatic servo system. An adaptive backstepping slide mode control method is proposed for pneumatic position servo system. The proposed method designs adaptive slide mode controller using backstepping design technique. The controller parameter adaptive law is derived from Lyapunov analysis to guarantee the stability of the system. A theorem is testified to show that the state of closed-loop system is uniformly bounded, and the closed-loop system is stable. The advantages of the proposed method include that system dynamic model parameters are not required for the controller design, uncertain parameters bounds are not need, and the bulk and expensive pressure sensor is not needed as well. Experimental results show that the designed controller can achieve better tracking performance, as compared with some existing methods.
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
Willigenburg, van L.G.; Vollebregt, H.M.; Sman, van der R.G.M.
An adaptive optimal scheduling and controller design is presented that attempts to improve the performance of beer membrane filtration over the ones currently obtained by operators. The research was performed as part of a large European research project called EU Cafe with the aim to investigate the
Maas, H.L.M.M.; Meiler, P.P.
This paper describes a concept to manage the information exchange between the operators and their consoles (the interface to the computer system) within a Command and Control (C2) centre. Application of his concept will result in a more effective and efficient information exchange, using adaptive in
Willigen, W.H. van; Schut, M.C.; Kester, L.J.H.M.
This paper is concerned with safety in (cooperative) adaptive cruise control systems. In these systems, the speed of the cars is maintained automatically, based on the preferred speed of the driver and the speed of the preceding car. Technologies that are used in these systems, such as radar and rad
慕小武; 虞继敏; 毕卫萍; 程代展
Robust adaptive control of nonholonomic systems in chained form with linearly parameterized and strongly nonlinear disturbance and drift terms is dicussed.The novelty of the proposed method is a combined use of the state-scaling and the back-stepping procedure.
Simonov, A.N.; Vdovine, G.V.; Loktev, M.
We present a prototype of an adaptive intraocular lens based on a modal liquid-crystal spatial phase modulator with wireless control. The modal corrector consists of a nematic liquid-crystal layer sandwiched between two glass substrates with transparent low- and high-ohmic electrodes, respectively.
Sheykhlouvand, Mohsen; Khalili, Erfan; Agha-Alinejad, Hamid; Gharaat, Mohammadali
This study compared the effects of 2 different high-intensity interval training (HIIT) programs in professional male canoe polo athletes. Responses of peak oxygen uptake (VO2peak), ventilatory threshold (VT), peak and mean anaerobic power output (PPO and MPO), blood volume, and hormonal adaptations to HIIT were examined. Male athletes (n = 21, age: 24 ± 3 years; height: 181 ± 4 cm; mass: 85 ± 6 kg; and body fat: 12.9 ± 2.7%) were randomly assigned to one of 3 groups (N = 7): (a) (G1) interval paddling with variable volume (6, 7, 8, 9, 9, 9, 8, 7, 6 repetitions per session from first to ninth session, respectively) × 60 second at lowest velocity that elicited VO2peak (vVO2peak), 1:3 work to recovery ratio; (b) (G2) interval paddling with variable intensity (6 × 60 second at 100, 110, 120, 130, 130, 130, 120, 110, 100% vVO2peak from first to ninth session, respectively, 1:3 work to recovery); and (c) (GCON) the control group performed three 60 minutes paddling sessions (75% vVO2peak) per week for 3 weeks. High-intensity interval training resulted in significant (except as shown) increases compared with pretest, in VO2peak (G1 = +8.8% and G2 = +8.5%), heart rate at VT (b·min) (G1 = +9.7% and G2 = +5.9%) and (%maximum) (G1 = +6.9%; p = 0.29 and G2 = +6.5%), PPO (G1 = +9.7% and G2 = +12.2%), MPO (G1 = +11.1%; p = 0.29 and G2 = +16.2%), total testosterone (G1 = +29.4% and G2 = +16.7%), total testosterone/cortisol ratio (G1 = +40.9% and G2 = +28.1%), and mean corpuscular hemoglobin (G1 = +1.7% and G2 = +1.3%). No significant changes were found in GCON. High-intensity interval paddling may improve both aerobic and anaerobic performances in professional male canoe polo athletes under the conditions of this study.
Full Text Available An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF. AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for active power filter. Simulation results demonstrate the feasibility and satisfactory performance of the proposed control strategies. It is shown that the proposed control method has an excellent dynamic performance such as small current tracking error, reduced total harmonic distortion (THD, and strong robustness in the presence of parameters variation and nonlinear load.
Folly, R.; Berlim, R.; Salgado, A.; Franca, R.; Valdman, B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Escola de Quimica
A fed-batch alcohol fermentation on a pilot plant scale with a digital supervisory control was evaluated as an experimental application case study of an adaptive controller. The verification of intrinsically dynamic variations in the characteristics of the fermentation, observed in previous work, showed the necessity of an adaptive control strategy for controller parameter tuning in order to adjust the changes in the specific rates of consumption, growth and product formation during the process. Satisfactory experimental results were obtained for set-point variations and sugar feed concentration load changes in the manipulated inlet flow to the fermenter. (author) 5 refs., 10 figs., 2 tabs.; e-mail: Valdman at H2O.EQ.UFRJ.BR
Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.
The key conclusions of this research are: 1. The EFXLMS algorithm demonstrated superior performance than the FXLMS algorithm during fast adaptive processes, in particular for non-stationary inputs. 2. Good attenuation of the peak. and root-mean-square (rms) values of the structural responses using the hybrid control system were observed for most of the real accelerograms. It was also observed that the hybrid control system always improved the performance of the passive contr...
Jiang, Yu; Jiang, Zhong-Ping
This paper studies the robust optimal control design for uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (robust-ADP). The objective is to fill up a gap in the past literature of ADP where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The...
Javaid, N.; Ahmad, A.; A. Rahim; Z.A. Khan; M. Ishfaq; Qasim, U.
Wireless Body Area Networks (WBANs) are widely used for applications such as modern health-care systems, where wireless sensors (nodes) monitor the parameter(s) of interest. Nodes are provided with limited battery power and battery power is dependent on radio activity. MAC protocols play a key role in controlling the radio activity. Therefore, we present Adaptive Medium Access Control (A-MAC) protocol for WBANs supported by linear programming models for the minimization of energy consumption ...
Pezzulo, G; Rigoli, F.; Friston, K.
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a...
Pornsin-Sirirak, T. N.; Tai, Y. C.; Nassef, H.; Ho, C M
This paper describes the first flexible parylene electrostatic actuator valves intended for micro adaptive flow control for the future use on the wings of micro-air-vehicle (MAV). The actuator diaphragm is made of two layers of parylene membranes with offset vent holes. Without electrostatic actuation, air can move freely from one side of the skin to the other side through the vent holes. With actuation, these vent holes are sealed and the airflow is controlled. The membrane behaves as a comp...
Milan Manojle Šunjevarić; Goran Z. Đukanović; Nataša M. Gospić
In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probabilit...
Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.
LU Minyue; GU Zhongquan
A decentralized generalized predictive control (GPC) algorithm is developed for strongly coupled multi-input multi-output systems with parallel computation. The algorithm is applied to adaptive control of structural vibration. The key steps in this algorithm are to group the actuators and the sensors and then to pair these groups into subsystems. It is important that the on-line identification and the control law design can be a parallel process for all these subsystems. It avoids the high computation cost in ordinary predictive control,and is of great advantage especially for large-scale systems.
Bartolini, G.; Levant, A.; Pisano, A.; Usai, E.
This paper endows the second-order sliding mode control (2-SMC) approach with additional capabilities of learning and control adaptation. We present a 2-SMC scheme that estimates and compensates for the uncertainties affecting the system dynamics. It also adjusts the discontinuous control effort online, so that it can be reduced to arbitrarily small values. The proposed scheme is particularly useful when the available information regarding the uncertainties is conservative, and the classical `fixed-gain' SMC would inevitably lead to largely oversized discontinuous control effort. Benefits from the viewpoint of chattering reduction are obtained, as confirmed by computer simulations.
Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These trainings vary from web-based cyber security trainings for control systems engineers to more advanced hands-on training that culminates with a Red Team/ Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors.
Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These training vary from web-based cyber security training for control systems engineers to more advanced hands-on training that culminates with a Red Team/Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors
EDF Operation and Engineering Company is the World's leading Nuclear Operator with the most important Nuclear fleet in Europe. Most of French operating nuclear plants were constructed within a small time window. Few new plants have come on line within the last decade. As a result, most operating plants today have an ageing workforce that is going to retire in large numbers. In the next ten years, 40% of EDF nuclear workforce is going to retire, in average 600 people per year and 1000 people at the peak. At the same time, EDF Company potential restructuring are opportunities to provide internal personnel for Nuclear Power Plants. The first generation of nuclear industry workforce was hired during nuclear plant starting and testing. That was an opportunity for training in the field without nuclear hazard. In addition, the NPP requirements increased dramatically through the last twenty years. This situation led to start a project to effectively adapt and renew workforce competences in the 19 EDF NPP in France. The presentation will focused on two main ways to achieve this goal. - A consistent program developed in 2007 to adapt our non-technical internal workforce for nuclear competences and skills needed. - A reliable Nuclear Educational and Training Program called 'Nuclear Academy' created for nuclear hired workforce based on team building, sister plants association, Senior workers and management presentations, and field training. (author)
Spyrou, Loukianos; Blokland, Yvonne; Farquhar, Jason; Bruhn, Jorgen
Brain-Computer Interface (BCI) systems are traditionally designed by taking into account user-specific data to enable practical use. More recently, subject independent (SI) classification algorithms have been developed which bypass the subject specific adaptation and enable rapid use of the system. A brain switch is a particular BCI system where the system is required to distinguish from two separate mental tasks corresponding to the on-off commands of a switch. Such applications require a low false positive rate (FPR) while having an acceptable response time (RT) until the switch is activated. In this work, we develop a methodology that produces optimal brain switch behavior through subject specific (SS) adaptation of: a) a multitrial prediction combination model and b) an SI classification model. We propose a statistical model of combining classifier predictions that enables optimal FPR calibration through a short calibration session. We trained an SI classifier on a training synchronous dataset and tested our method on separate holdout synchronous and asynchronous brain switch experiments. Although our SI model obtained similar performance between training and holdout datasets, 86% and 85% for the synchronous and 69% and 66% for the asynchronous the between subject FPR and TPR variability was high (up to 62%). The short calibration session was then employed to alleviate that problem and provide decision thresholds that achieve when possible a target FPR=1% with good accuracy for both datasets. PMID:26529768
朱雅光; 金波; 李伟
Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance control is established. Then, the indirect adaptive control algorithm is derived. Through the analysis of its parameters, it can be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. Therefore, the fuzzy control algorithm is used to adjust the adaptive control parameters. The satisfied system response can be obtained based on the adjustment in real time according to the error between input and output. Comparative experiments and analysis of traditional adaptive control and the improved adaptive control algorithm are presented. It can be verified that not only desired contact force can be reached quickly in different environments, but also smaller contact impact and sliding avoidance are guaranteed, which means that the control strategy has great significance to enhance the adaptability of the hexapod robot.
Nagle, Aniket; Riener, Robert; Wolf, Peter
Computer games are increasingly being used for training cognitive functions like working memory and attention among the growing population of older adults. While cognitive training games often include elements like difficulty adaptation, rewards, and visual themes to make the games more enjoyable and effective, the effect of different degrees of afforded user control in manipulating these elements has not been systematically studied. To address this issue, two distinct implementations of the ...
Aniket eNagle; Robert eRiener; Peter eWolf
Computer games are increasingly being used for training cognitive functions like working memory and attention among the growing population of older adults. While cognitive training games often include elements like difficulty adaptation, rewards, and visual themes to make the games more enjoyable and effective, the effect of different degrees of afforded user control in manipulating these elements has not been systematically studied. To address this issue, two distinct implementations of the ...
Full Text Available The aim of the study was to compare the effects of plyometric training using 30, 60, or 120 s of rest between sets on explosive adaptations in young soccer players. Four groups of athletes (age 10.4 ± 2.3 y; soccer experience 3.3 ± 1.5 y were randomly formed: control (CG; n = 15, plyometric training with 30 s (G30; n = 13, 60 s (G60; n = 14, and 120 s (G120; n = 12 of rest between training sets. Before and after intervention players were measured in jump ability, 20-m sprint time, change of direction speed (CODS, and kicking performance. The training program was applied during 7 weeks, 2 sessions per week, for a total of 840 jumps. After intervention the G30, G60 and G120 groups showed a significant (p = 0.0001 – 0.04 and small to moderate effect size (ES improvement in the countermovement jump (ES = 0.49; 0.58; 0.55, 20 cm drop jump reactive strength index (ES = 0.81; 0.89; 0.86, CODS (ES = -1.03; -0.87; -1.04, and kicking performance (ES = 0.39; 0.49; 0.43, with no differences between treatments. The study shows that 30, 60, and 120 s of rest between sets ensure similar significant and small to moderate ES improvement in jump, CODS, and kicking performance during high-intensity short-term explosive training in young male soccer players.
Mohamed Said Sayed Ahmed; Ping Zhang; Yun-Jie Wu
A modified adaptive two-phase sliding mode controller for the synchronous motor drive that is highly robust to uncertain-ties and external disturbances is proposed in this paper. The proposed controller uses two-phase sliding mode control (SMC) where the 1st phase mainly controls the system in steady states and disturbed states-it is a smoothing phase. The 2nd phase is used mainly in the case of disturbed states. Also, it is an autotuning phase and uses a simple adaptive algorithm to tune the gain of conventional variable structure control (VSC). The modified controller is useful in position control of a permanent magnet synchronous drive.
Shieh, M-Y; Chang, K-H [Department of E. E., Southern Taiwan University, 1 Nantai St., YungKang City, Tainan County 71005, Taiwan (China); Lia, Y-S [Executive Director Office, ITRI, Southern Taiwan Innovation Park, Tainan County, Taiwan (China)], E-mail: firstname.lastname@example.org
This paper proposes a method for the design of a biped locomotion controller based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) inverse learning model. In the model developed here, an integrated ANFIS structure is trained to function as the system identifier for the modeling of the inverse dynamics of a biped robot. The parameters resulting from the modeling process are duplicated and integrated as those of the biped locomotion controller to provide favorable control action. As the simulation results show, the proposed controller is able to generate a stable walking cycle for a biped robot. Moreover, the experimental results demonstrate that the performance of the proposed controller is satisfactory under conditions when the robot stands in different postures or moves on a rugged surface.
Hosseini, S.H.; Etemadi, A.H. [Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran)
Fixed gain controllers for automatic generation control are designed at nominal operating conditions and fail to provide best control performance over a wide range of operating conditions. So, to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to compute control gains. A control scheme based on artificial neuro-fuzzy inference system (ANFIS), which is trained by the results of off-line studies obtained using particle swarm optimization, is proposed in this paper to optimize and update control gains in real-time according to load variations. Also, frequency relaxation is implemented using ANFIS. The efficiency of the proposed method is demonstrated via simulations. Compliance of the proposed method with NERC control performance standard is verified. (author)
Hao, Lina; Sun, Zhiyong; Li, Zhi; Su, Yunquan; Gao, Jianchao
IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable.
Oveisi, Atta; Nestorović, Tamara
In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.
Full Text Available Given the importance of effective treatments for children with reading impairment, paired with growing concern about the lack of scientific replication in psychological science, the aim of this study was to replicate a quasi-randomised trial of sight word and phonics training using a randomised controlled trial (RCT design. One group of poor readers (N = 41 did 8 weeks of phonics training (i.e., phonological decoding and then 8 weeks of sight word training (i.e., whole-word recognition. A second group did the reverse order of training. Sight word and phonics training each had a large and significant valid treatment effect on trained irregular words and word reading fluency. In addition, combined sight word and phonics training had a moderate and significant valid treatment effect on nonword reading accuracy and fluency. These findings demonstrate the reliability of both phonics and sight word training in treating poor readers in an era where the importance of scientific reliability is under close scrutiny.
van Dijk, Ludger; van der Sluis, Corry K.; van Dijk, Hylke W.; Bongers, Raoul M.
Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs. PMID:27556154
van Dijk, Ludger; van der Sluis, Corry K; van Dijk, Hylke W; Bongers, Raoul M
Video games that aim to improve myoelectric control (myogames) are gaining popularity and are often part of the rehabilitation process following an upper limb amputation. However, direct evidence for their effect on prosthetic skill is limited. This study aimed to determine whether and how myogaming improves EMG control and whether performance improvements transfer to a prosthesis-simulator task. Able-bodied right-handed participants (N = 28) were randomly assigned to 1 of 2 groups. The intervention group was trained to control a video game (Breakout-EMG) using the myosignals of wrist flexors and extensors. Controls played a regular Mario computer game. Both groups trained 20 minutes a day for 4 consecutive days. Before and after training, two tests were conducted: one level of the Breakout-EMG game, and grasping objects with a prosthesis-simulator. Results showed a larger increase of in-game accuracy for the Breakout-EMG group than for controls. The Breakout-EMG group moreover showed increased adaptation of the EMG signal to the game. No differences were found in using a prosthesis-simulator. This study demonstrated that myogames lead to task-specific myocontrol skills. Transfer to a prosthesis task is therefore far from easy. We discuss several implications for future myogame designs. PMID:27556154
McFarland, Michael Bryan
Research has shown that neural networks can be used to improve upon approximate dynamic inversion for control of uncertain nonlinear systems. In one architecture, the neural network adaptively cancels inversion errors through on-line learning. Such learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring stability of the closed-loop system. In this research, previous results using linear-in-parameters neural networks were reformulated in the context of a more general class of composite nonlinear systems, and the control scheme was shown to possess important similarities and major differences with established methods of adaptive control. The neural-adaptive nonlinear control methodology in question has been used to design an autopilot for an anti-air missile with enhanced agile maneuvering capability, and simulation results indicate that this approach is a feasible one. There are, however, certain difficulties associated with choosing the proper network architecture which make it difficult to achieve the rapid learning required in this application. Accordingly, this technique has been further extended to incorporate the important class of feedforward neural networks with a single hidden layer. These neural networks feature well-known approximation capabilities and provide an effective, although nonlinear, parameterization of the adaptive control problem. Numerical results from a six-degree-of-freedom nonlinear agile anti-air missile simulation demonstrate the effectiveness of the autopilot design based on multilayer networks. Previous work in this area has implicitly assumed precise knowledge of the plant order, and made no allowances for unmodeled dynamics. This thesis describes an approach to the problem of controlling a class of nonlinear systems in the face of both unknown nonlinearities and unmodeled dynamics. The proposed methodology is similar to robust adaptive control techniques derived for control of linear
Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna
Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.
Juan C. Tudón-Martínez
Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.
Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.
Basar, T. [Univ. of Illinois, Urbana, IL (United States)
We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.
REN Liyong; LU Xianliang; WEI Qingsong; ZHOU Xu
To solve the problem that most of existing layered multicast protocols cannot adapt to dynamic network conditions because their layers are coarsely granulated and static, a new congestion control mechanism for dynamic adaptive layered multicast(DALM) is presented. In this mechanism, a novel feedback aggregating algorithm is put forward, which can dynamically determine the number of layers and the rate of each layer, and can efficiently improve network bandwidth utilization ratio.Additionally, because all layers is transmitted in only one group, the intricate and time-consuming internet group management protocol(IGMP) operations, caused by receiver joining a new layer or leaving the topmost subscribed layer, are thoroughly eliminated. And this mechanism also avoids other problems resulted from multiple groups. Simulation results show that DALM is adaptive and TCP friendly.
Khizhnyak, Anatoliy; Markov, Vladimir
Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.
This paper presents a feedback nonlinear control law for a train-like vehicle (TLV) used in nuclear power-station maintenance. The front cart is either manual or automated guided. The rear carts are feedback controlled. The control objective is to ensure that the rear carts track the path produced (on-line) by the front cart. This controller was experimentally tested on the TLV-prototype. (authors). 4 figs., 4 refs
This volume is a study guide for training Radiological Control Technicians. Provided herein are support materials for learning radiological documentation, communication systems, counting errors and statistics, dosimetry, contamination control, airborne sampling program methods, respiratory protection, radiological source control, environmental monitoring, access control and work area setup, radiological work coverage, shipment and receipt for radioactive material, radiological incidents and emergencies, personnel decontamination, first aid, radiation survey instrumentation, contamination monitoring, air sampling, and counting room equipment
Full Text Available An adaptive gain sliding observer for uncertain parameter nonlinear systems together with an adaptive gain sliding controller is proposed in this paper. It considered nonlinear, SISO affine systems, with uncertainties in steady-state functions and parameters. A further parameter term, adaptively updated, has been introduced in steady state space model of the controlled system, in order to obtain useful information despite fault detection and isolation. By using of the sliding observer with adaptive gain, the robustness to uncertainties is increased and the parameters adaptively updated can provide useful information in fault detection. Also, the state estimation error is bounded accordingly with bound limits of the uncertainties. The both of them, the sliding adaptive observer and sliding controller are designed to fulfill the attractiveness condition of its corresponding switching surface. An application to a single arm with flexible joint robot is presented. In order to alleviate chattering, a parameterized tangent hyperbolic has been used as switching function, instead of pure relay one, to the observer and the controller. Also, the gains of the switching functions, to the sliding observer and sliding controller are adaptively updated depending of estimation error and tracking error, respectively. By the using adaptive gains, the transient and tracking response can be improved.
TANG Tao; LI Ke-Ping
This paper presents a new cellular automaton (CA) model for train control system simulation.In the proposed CA model,the driver reactions to train movements are captured by some updated rules.The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow.A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic.Not only the characteristic behavior of railway traffic flow can be reproduced,but also the simulation values of the minimum time headway are close to the theoretical values.
This paper presents a new cellular automaton (CA) model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.
Full Text Available To alleviate the limitations of statistical based methods of forecasting of exchange rates, soft and evolutionary computing based techniques have been introduced in the literature. To further the research in this direction this paper proposes a simple but promising hybrid prediction model by suitably combining an adaptive autoregressive moving average (ARMA architecture and differential evolution (DE based training of its feed-forward and feed-back parameters. Simple statistical features are extracted for each exchange rate using a sliding window of past data and are employed as input to the prediction model for training its internal coefficients using DE optimization strategy. The prediction efficiency is validated using past exchange rates not used for training purpose. Simulation results using real life data are presented for three different exchange rates for one–fifteen months’ ahead predictions. The results of the developed model are compared with other four competitive methods such as ARMA-particle swarm optimization (PSO, ARMA-cat swarm optimization (CSO, ARMA-bacterial foraging optimization (BFO and ARMA-forward backward least mean square (FBLMS. The derivative based ARMA-FBLMS forecasting model exhibits worst prediction performance of the exchange rates. Comparisons of different performance measures including the training time of the all three evolutionary computing based models demonstrate that the proposed ARMA-DE exchange rate prediction model possesses superior short and long range prediction potentiality compared to others.
Romero-Arenas, Salvador; Martínez-Pascual, Miryam; Alcaraz, Pedro E.
Declines in maximal aerobic power and skeletal muscle force production with advancing age are examples of functional declines with aging, which can severely limit physical performance and independence, and are negatively correlated with all cause mortality. It is well known that both endurance exercise and resistance training can substantially improve physical fitness and health-related factors in older individuals. Circuit-based resistance training, where loads are lifted with minimal rest, may be a very effective strategy for increasing oxygen consumption, pulmonary ventilation, strength, and functional capacity while improving body composition. In addition, circuit training is a time-efficient exercise modality that can elicit demonstrable improvements in health and physical fitness. Hence, it seems reasonable to identify the most effective combination of intensity, volume, work to rest ratio, weekly frequency and exercise sequence to promote neuromuscular, cardiorespiratory and body composition adaptations in the elderly. Thus, the purpose of this review was to summarize and update knowledge about the effects of circuit weight training in older adults and elderly population, as a starting point for developing future interventions that maintain a higher quality of life in people throughout their lifetime. PMID:24124631
Spaccavento, Simona; Cellamare, Fara; Cafforio, Elisabetta; Loverre, Anna; Craca, Angela
Unilateral spatial neglect consists of the inability of a patient to respond, orient, and attend to stimuli on the left side of a space following a right-hemisphere lesion. Many rehabilitation approaches have been proposed to reduce neglect. The aim of our study was to compare the effect of visual-scanning training (VST) and prismatic adaptation (PA) on patients with neglect following a right-hemisphere lesion. Twenty patients with left neglect were enrolled in the study. Before and after training, a comprehensive neuropsychological assessment of visuospatial abilities, evaluating personal, peripersonal, and extrapersonal neglect, was performed. After assessment, patients were alternately assigned to 1 of 2 groups, VST or PA. Both trainings consisted of 20 sessions, 1 per day, 5 days a week for 4 weeks. The results showed that both treatments improved patient neglect, especially in personal and peripersonal spaces. No difference between pretreatment and posttreatment was found in extrapersonal subscales. This finding could be due to the fact that there were no exercises requiring the use of objects within reach in either training. In conclusion, no difference between the 2 approaches was found, and both are useful rehabilitation techniques that appear to improve neglect.
It is the purpose of this paper to address the issue of training for power plant personnel in the area of hydrogen control. The authors experience in the training business indicates that most of the operations and engineering personnel have a very limited awareness of this phenomenon. Topics discussed in this paper include: 1) theory of hydrogen combustion kinetics; 2) incidents involving hydrogen combustion events; 3) normal operations interfacing with hydrogen; 4) accident conditions; and 5) mitigation schemes
Wang, Zhen; Wu, Zhong; Du, Yijiang
During the reentry process of reusable launch vehicles (RLVs), the large range of flight envelope will not only result in high nonlinearities, strong coupling and fast time-varying characteristics of the attitude dynamics, but also result in great uncertainties in the atmospheric density, aerodynamic coefficients and environmental disturbances, etc. In order to attenuate the effects of these problems on the control performance of the reentry process, a robust adaptive backstepping control (RABC) strategy is proposed for RLV in this paper. This strategy consists of two-loop controllers designed via backstepping method. Both the outer and the inner loop adopt a robust adaptive controller, which can deal with the disturbances and uncertainties by the variable-structure term with the estimation of their bounds. The outer loop can track the desired attitude by the design of virtual control-the desired angular velocity, while the inner one can track the desired angular velocity by the design of control torque. Theoretical analysis indicates that the closed-loop system under the proposed control strategy is globally asymptotically stable. Even if the boundaries of the disturbances and uncertainties are unknown, the attitude can track the desired value accurately. Simulation results of a certain RLV demonstrate the effectiveness of the control strategy.
Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.
Poyneer, L A; Veran, J
We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.
Mohktar, Ruzaidi A M; Montgomery, Magda K; Murphy, Robyn M; Watt, Matthew J
Cytoplasmic lipid droplets provide a reservoir for triglyceride storage and are a central hub for fatty acid trafficking in cells. The protein perilipin 5 (PLIN5) is highly expressed in oxidative tissues such as skeletal muscle and regulates lipid metabolism by coordinating the trafficking and the reversible interactions of effector proteins at the lipid droplet. PLIN5 may also regulate mitochondrial function, although this remains unsubstantiated. Hence, the aims of this study were to examine the role of PLIN5 in the regulation of skeletal muscle substrate metabolism during acute exercise and to determine whether PLIN5 is required for the metabolic adaptations and enhancement in exercise tolerance following endurance exercise training. Using muscle-specific Plin5 knockout mice (Plin5(MKO)), we show that PLIN5 is dispensable for normal substrate metabolism during exercise, as reflected by levels of blood metabolites and rates of glycogen and triglyceride depletion that were indistinguishable from control (lox/lox) mice. Plin5(MKO) mice exhibited a functional impairment in their response to endurance exercise training, as reflected by reduced maximal running capacity (20%) and reduced time to fatigue during prolonged submaximal exercise (15%). The reduction in exercise performance was not accompanied by alterations in carbohydrate and fatty acid metabolism during submaximal exercise. Similarly, mitochondrial capacity (mtDNA, respiratory complex proteins, citrate synthase activity) and mitochondrial function (oxygen consumption rate in muscle fiber bundles) were not different between lox/lox and Plin5(MKO) mice. Thus, PLIN5 is dispensable for normal substrate metabolism during exercise and is not required to promote mitochondrial biogenesis or enhance the cellular adaptations to endurance exercise training.
Mohktar, Ruzaidi A M; Montgomery, Magda K; Murphy, Robyn M; Watt, Matthew J
Cytoplasmic lipid droplets provide a reservoir for triglyceride storage and are a central hub for fatty acid trafficking in cells. The protein perilipin 5 (PLIN5) is highly expressed in oxidative tissues such as skeletal muscle and regulates lipid metabolism by coordinating the trafficking and the reversible interactions of effector proteins at the lipid droplet. PLIN5 may also regulate mitochondrial function, although this remains unsubstantiated. Hence, the aims of this study were to examine the role of PLIN5 in the regulation of skeletal muscle substrate metabolism during acute exercise and to determine whether PLIN5 is required for the metabolic adaptations and enhancement in exercise tolerance following endurance exercise training. Using muscle-specific Plin5 knockout mice (Plin5(MKO)), we show that PLIN5 is dispensable for normal substrate metabolism during exercise, as reflected by levels of blood metabolites and rates of glycogen and triglyceride depletion that were indistinguishable from control (lox/lox) mice. Plin5(MKO) mice exhibited a functional impairment in their response to endurance exercise training, as reflected by reduced maximal running capacity (20%) and reduced time to fatigue during prolonged submaximal exercise (15%). The reduction in exercise performance was not accompanied by alterations in carbohydrate and fatty acid metabolism during submaximal exercise. Similarly, mitochondrial capacity (mtDNA, respiratory complex proteins, citrate synthase activity) and mitochondrial function (oxygen consumption rate in muscle fiber bundles) were not different between lox/lox and Plin5(MKO) mice. Thus, PLIN5 is dispensable for normal substrate metabolism during exercise and is not required to promote mitochondrial biogenesis or enhance the cellular adaptations to endurance exercise training. PMID:27189934
Full Text Available To maintain balance during locomotion, the central nervous system (CNS accommodates changes in the constraints of spatial environment (e.g., existence of an obstacle or changes in the surface properties. Locomotion while modifying the basic movement patterns in response to such constraints is referred to as adaptive locomotion. The most powerful means of ensuring balance during adaptive locomotion is to visually perceive the environmental properties at a distance and modify the movement patterns in an anticipatory manner to avoid perturbation altogether. For this reason, visuomotor control of adaptive locomotion is characterized, at least in part, by its anticipatory nature. The purpose of the present article is to review the relevant studies which revealed the anticipatory nature of the visuomotor control of adaptive locomotion. The anticipatory locomotor adjustments for stationary and changeable environment, as well as the spatio-temporal patterns of gaze behavior to support the anticipatory locomotor adjustments are described. Such description will clearly show that anticipatory locomotor adjustments are initiated when an object of interest (e.g., a goal or obstacle still exists in far space. This review also show that, as a prerequisite of anticipatory locomotor adjustments, environmental properties are accurately perceived from a distance in relation to individual’s action capabilities.
Engel, E.; Kovalev, I. V.; Karandeev, D.
The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.
Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang
Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.
WANG Xue-song; CHENG Yu-hu; SUN Wei
Aimed at the lack of self-tuning PID parameters in conventional PID controllers, the structure and learning algorithm of an adaptive PID controller based on reinforcement learning were proposed. Actor-Critic learning was used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency,a single RBF neural network was used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for complex nonlinear systems and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.
Yugang NIU; Xingyu WANG; Junwei LU
A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, I.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to nake the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.
Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S
As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. PMID:22275543
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.
... flexible service options responsive to customer needs. The advent of microprocessor- based electronic.... However, the lack of an effective collision avoidance system allowed the continued occurrence of accidents... control systems without impairing technological development. 70 FR 11,052 (Mar. 7, 2005). FRA...
... control systems. See 70 FR 11,052 (Mar. 7, 2005) (codified at 49 CFR part 236, subpart H). As a..., 2015. 75 FR 2598 (Jan. 15, 2010). Under RSIA, such PTC implementation must be completed by each Class I... 13563 on January 18, 2011 (76 FR 3821 (Jan. 21, 2011)), which outlined a plan to improve regulations...
Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.
Full Text Available This work presents the use of a hybrid-neural model for predictive control of a plug flow polymerisation reactor. The hybrid-neural model (HNM is based on fundamental conservation laws associated with a neural network (NN used to model the uncertain parameters. By simulations, the performance of this approach was studied for a peroxide-initiated styrene tubular reactor. The HNM was synthesised for a CSTR reactor with a radial basis function neural net (RBFN used to estimate the reaction rates recursively. The adaptive HNM was incorporated in two model predictive control strategies, a direct synthesis scheme and an optimum steady state scheme. Tests for servo and regulator control showed excellent behaviour following different setpoint variations, and rejecting perturbations. The good generalisation and training capacities of hybrid models, associated with the simplicity and robustness characteristics of the MPC formulations, make an attractive combination for the control of a polymerisation reactor.
Curzi, Davide; Baldassarri, Valentina; De Matteis, Rita; Salamanna, Francesca; Bolotta, Alessandra; Frizziero, Antonio; Fini, Milena; Marini, Marina; Falcieri, Elisabetta
Myotendinous junction is the muscle-tendon interface through which the contractile force can be transferred from myofibrils to the tendon extracellular matrix. At the ultrastructural level, aerobic training can modify the distal myotendinous junction of rat gastrocnemius, increasing the contact area between tissues. The aim of this work is to investigate the correlation between morphological changes and protein modulation of the myotendinous junction following moderate training. For this reason, talin, vinculin and type IV collagen amount and spatial distribution were investigated by immunohistochemistry and confocal microscopy. The images were then digitally analyzed by evaluating fluorescence intensity. Morphometric analysis revealed a significant increased thickening of muscle basal lamina in the trained group (53.1 ± 0.4 nm) with respect to the control group (43.9 ± 0.3 nm), and morphological observation showed the presence of an electron-dense area in the exercised muscles, close to the myotendinous junction. Protein concentrations appeared significantly increased in the trained group (talin +22.2%; vinculin +22.8% and type IV collagen +11.8%) with respect to the control group. Therefore, our findings suggest that moderate aerobic training induces/causes morphological changes at the myotendinous junction, correlated to the synthesis of structural proteins of the muscular basal lamina and of the cytoskeleton.
DNA damage triggers surveillance mechanisms, the DNA checkpoints, that control the genome integrity. The DNA checkpoints induce several responses, either cellular or transcriptional, that favor DNA repair. In particular, activation of the DNA checkpoints inhibits cell cycle progression in all phases, depending on the stage when lesions occur. These arrests are generally transient and cells ultimately reenter the cell division cycle whether lesions have been repaired (this process is termed 'recovery') or have proved un-repairable (this option is called 'adaptation'). The mechanisms controlling cell cycle arrests, recovery and adaptation are largely conserved among eukaryotes, and much information is now available for the yeast Saccharomyces cerevisiae, that is used as a model organism in these studies. (author)
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Olaf Mühling; Ralf Ruhmann; Arno Seeboth
The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from...
Full Text Available A direct model reference adaptive controller (MRAC is derived for an underwater vehicle with significant thruster dynamics and limited thruster power. The reference model decomposition (RMD technique is used to compensate for the thruster dynamics. A reference model adjustment (RMA technique modifying the reference model acceleration is used to avoid thruster saturation. The design methods are simulated for the yawing motion of an underwater vehicle.
Thor I. Fossen
Full Text Available Robust adaptive control of underwater vehicles in 6 DOF is analysed in the context of measurement noise. The performance of the adaptive control laws of Sadegh and Harowitz (1990 and Slotine and Benedetto (1990 are compared. Both these schemes require that all states are measured, that is the velocities and positions in surge, sway, heave, roll, pitch and yaw. However, for underwater vehicles it is difficult to measure the linear velocities whereas angular velocity measurements can be obtained by using a 3 axes angular rate sensor. This problem is addressed by designing a nonlinear observer for linear velocity state estimation. The proposed observer requires that the position and the attitude are measured, e.g. by using a hydroacoustic positioning system for linear positions, two gyros for roll and pitch and a compass for yaw. In addition angular rate measurements will be assumed available from a 3-axes rate sensor or a state estimator. It is also assumed that the measurement rate is limited to 2 Hz for all the sensors. Simulation studies with a 3 DOF AUV model are used to demonstrate the convergence and robustness of the adaptive control laws and the velocity state observer.
Li, Shuhui; Wang, Jian
We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, “up-down” power multicasting and “ladder” power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251
Full Text Available Deficits in inhibitory control, the ability to suppress ongoing or planned motor or cognitive processes, contribute to many psychiatric and neurological disorders. The rehabilitation of inhibition-related disorders may therefore benefit from neuroplasticity-based training protocols aiming at normalizing inhibitory control proficiency and the underlying brain networks. Current literature on training-induced behavioral and brain plasticity in inhibitory control suggests that improvements may follow either from the development of automatic forms of inhibition or from the strengthening of top-down, controlled inhibition. Automatic inhibition develops in conditions of consistent and repeated associations between inhibition-triggering stimuli and stopping goals. Once established, the stop signals directly elicit inhibition, thereby bypassing slow, top-down executive control and accelerating stopping processes. In contrast, training regimens involving varying stimulus-response associations or frequent inhibition failures prevent the development of automatic inhibition and thus strengthen top-down inhibitory processes rather than bottom-up ones. We discuss these findings in terms of developing optimal inhibitory control training regimens for rehabilitation purposes.
Trong-Toan TRAN; Shuzhi Sam GE; Wei HE
In this paper, we address the control problem of an uncertain robotic manipulator with input saturations, unknown input scalings and disturbances. For this purpose, a model reference adaptive control like (MRAC-like) is used to handle the input saturations. The model reference is input to state stable (ISS) and driven by the errors between the required control signals and input saturations. The uncertain parameters are dealt with by using linear-in-the-parameters property of robotic dynamics, while unknown input scalings and disturbances are handled by non-regressor based approach. Our design ensures that all the signals in the closed-loop system are bounded, and the tracking error converges to the compact set which depends on the predetermined bounds of the control inputs. Simulation on a planar elbow manipulator with two joints is provided to illustrate the effectiveness of the proposed controller.
Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.
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
Stallknecht, B; Roesdahl, M; Vinten, J;
Physical training increases insulin stimulated glucose uptake in adipocytes and decreases insulin secretion from pancreatic islets. The mechanism behind these adaptations is not known. Because in acute exercise adrenergic activity influences both adipocytes and pancreatic islets, the sympathetic...... in sham adrenodemedullated rats (P muscle noradrenaline content in sympathectomized leg was 9% of content in sham sympathectomized leg (P trained for 10 weeks or remained sedentary. Insulin stimulated 3-O-[14C]methylglucose transport...... that adrenergic activity is not important for the training induced decrease in size and increase in insulin stimulated glucose transport of adipocytes. Neither is an intact adrenal medulla necessary for training-induced adaptations in pancreatic beta cell function. Finally, in response to training, beta cell...
Full Text Available This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC of 3-phase Induction Motor (IM under open-phase fault (unbalanced or faulty IM. The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
Cochran, Andrew J R; Percival, Michael E; Tricarico, Steven; Little, Jonathan P; Cermak, Naomi; Gillen, Jenna B; Tarnopolsky, Mark A; Gibala, Martin J
High-intensity interval training (HIIT) performed in an 'all-out' manner (e.g. repeated Wingate tests) is a time-efficient strategy to induce skeletal muscle remodelling towards a more oxidative phenotype. A fundamental question that remains unclear, however, is whether the intermittent or 'pulsed' nature of the stimulus is critical to the adaptive response. In study 1, we examined whether the activation of signalling cascades linked to mitochondrial biogenesis was dependent on the manner in which an acute high-intensity exercise stimulus was applied. Subjects performed either four 30 s Wingate tests interspersed with 4 min of rest (INT) or a bout of continuous exercise (CONT) that was matched for total work (67 ± 7 kJ) and which required ∼4 min to complete as fast as possible. Both protocols elicited similar increases in markers of adenosine monophosphate-activated protein kinase (AMPK) and p38 mitogen-activated protein kinase activation, as well as Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) mRNA expression (main effects for time, P ≤ 0.05). In study 2, we determined whether 6 weeks of the CONT protocol (3 days per week) would increase skeletal muscle mitochondrial content to a similar extent to what we have previously reported after 6 weeks of INT. Despite similar acute signalling responses to the CONT and INT protocols, training with CONT did not increase the maximal activity or protein content of a range of mitochondrial markers. However, peak oxygen uptake was higher after CONT training (from 45.7 ± 5.4 to 48.3 ± 6.5 ml kg(-1) min(-1); P muscle adaptations to low-volume, all-out HIIT. Despite the lack of skeletal muscle mitochondrial adaptations, our data show that a training programme based on a brief bout of high-intensity exercise, which lasted <10 min per session including warm-up, and performed three times per week for 6 weeks, improved peak oxygen uptake in young healthy subjects.
PEI Bingnan; LI Chuanguang
A modified LMS algorithm for noise-control is suggested after a mathematical model ofsound-cancellation is established, on the basis of thesound wave interference principle and the physicalmodel of progressive waves in a duct. Its applicationin controlling noise with the frequency range from 100to 800 Hz can be implemented by using the adaptivedigital signal processing technique. The experimentson a pink noise, a broadband noise and a noise takenfrom a tank were made, which show that there existsan attenuation of 11 dB at the frequency of 500 Hzor so, and that the proposed adaptive noise controltechnique is very effective and valid.
Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.
Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.
Kallesøe, Carsten; Jensen, Tom Nørgaard; Wisniewski, Rafal
Water scarcity is an increasing problem worldwide and at the same time a huge amount of water is lost through leakages in the distribution network. It is well known that improved pressure control can lower the leakage problems. In this work water networks with a single pressure actuator and several....... Subsequently, these relations are exploited in an adaptive reference control scheme for the actuator pressure that ensures constant pressure at the critical points. Numerical experiments underpin the results. © Copyright IEEE - All rights reserved....
Ortega, Pedro A
Explaining adaptive behavior is a central problem in artificial intelligence research. Here we formalize adaptive agents as mixture distributions over sequences of inputs and outputs (I/O). Each distribution of the mixture constitutes a 'possible world', but the agent does not know which of the possible worlds it is actually facing. The problem is to adapt the I/O stream in a way that is compatible with the true world. A natural measure of adaptation can be obtained by the Kullback-Leibler (KL) divergence between the I/O distribution of the true world and the I/O distribution expected by the agent that is uncertain about possible worlds. In the case of pure input streams, the Bayesian mixture provides a well-known solution for this problem. We show, however, that in the case of I/O streams this solution breaks down, because outputs are issued by the agent itself and require a different probabilistic syntax as provided by intervention calculus. Based on this calculus, we obtain a Bayesian control rule that all...
Kloepper, Laura N; Smith, Adam B; Nachtigall, Paul E; Buck, John R; Simmons, James A; Pacini, Aude F
Echolocating animals adjust the transmit intensity and receive sensitivity of their sonar in order to regulate the sensation level of their echoes; this process is often termed automatic gain control. Gain control is considered not to be under the animal's cognitive control, but previous investigations studied animals ensonifying targets or hydrophone arrays at predictable distances. To test whether animals maintain gain control at a fixed level in uncertain conditions, we measured changes in signal intensity for a bottlenose dolphin (Tursiops truncatus) detecting a target at three target distances (2.5, 4 and 7 m) in two types of sessions: predictable and unpredictable. Predictable sessions presented the target at a constant distance; unpredictable sessions moved the target randomly between the three target positions. In the predictable sessions the dolphin demonstrated intensity distance compensation, increasing the emitted click intensity as the target distance increased. Additionally, as trials within sessions progressed, the animal adjusted its click intensity even from the first click in a click train, which is consistent with the animal expecting a target at a certain range. In the unpredictable sessions there was no significant difference of intensity with target distance until after the 7th click in a click train. Together, these results demonstrate that the bottlenose dolphin uses learning and expectation for sonar gain control.
Møller, Mathias Bech; Kjær, Michael; Svensson, René Brüggebusch;
BACKGROUND: tendon and skeletal muscle function adapts to physical training of resistive nature, but it is unknown to what extent persons with genetically altered connective tissue - who have a higher than normal tendon extensibility - will obtain any effect upon their tendon and muscle when...... undergoing muscle strength training. We investigated patients with classical Ehlers Danlos Syndrome (EDS) (collagen type V defect) who display articular hypermobility, skin extensibility and tissue fragility. METHODS: subjects underwent strength training 3 times a week for 4 months and were tested before...... patients, and the results indicated that both tendon and skeletal muscle properties can be improved also in this patient group when they are subjected to resistance training....
Full Text Available Abstract The objective of the present study was to evaluate the effects of 8-week balance or weight training on ankle joint stiffness and limb stability for older adults, furthermore, on outcomes of slips while walking. Eighteen older adults volunteered for the study and randomly were assigned to the three groups, such as, weight, balance, or control group. While walking on a walking track, three-dimensional posture data were sampled and ankle joint stiffness and limb stability were computed to evaluate the effects of training. 2 (pre and post × 3 (weight, balance, and control × 2 (dominant and non-dominant legs mixed factor repeated ANOVA was performed. The results indicated that only balance training group showed an improvement in joint stiffness and both the training groups showed improvements in limb stability. Also, fall frequency results suggested that joint stiffness and limb stability had an effect on the likelihood of slip-induced falls. In conclusion, training can facilitate improvements in joint and limb control mechanism for older adults contributing to an improvement in the likelihood of slip-induced falls.
Berkhoff, A.P.; Wesselink, J.M.
Model errors in multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations may lead to unstable systems or increased error signals. In this paper, a combination of high-authority control (HAC) and low-authority control (LAC) is considered for improved perform
Li, Ning; Cao, Jinde
In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765
Wai, Rong-Jong; Lee, Jeng-Dao
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. PMID:18269938
Sri Latha Eti
Full Text Available Brushless DC Motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper proposed an improved Adaptive Fuzzy PI controller to control the speed of BLDC motor. This paper provides an overview of different tuning methods of PID Controller applied to control the speed of the transfer function model of the BLDC motor drive and then to the mathematical model of the BLDC motor drive. It is difficult to tune the parameters and get satisfied control characteristics by using normal conventional PI controller. The experimental results verify that Adaptive Fuzzy PI controller has better control performance than the conventional PI controller. The modeling, control and simulation of the BLDC motor have been done using the MATLAB/SIMULINK software. Also, the dynamic characteristics of the BLDC motor (i.e. speed and torque as well as currents and voltages of the inverter components are observed by using the developed model.