897 resultados para Control of Quantities and Costs


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A dynamic model and control system of an artificial muscle is presented. The artificial muscle is based on a contractile polymer gel which undergoes abrupt volume changes in response to variations in external conditions. The device uses an acid-base reaction to directly convert chemical to mechanical energy. A nonlinear sliding mode control system is proposed to track desired joint trajectories of a single link controlled by two antagonist muscles. Both the model and controller were implemented and produced acceptable tracking performance at 2Hz.

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This thesis presents methods for implementing robust hexpod locomotion on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degrees of freedom, and 8 on board computers. We investigate the following topics in depth: distributed control of a complex robot, insect-inspired locomotion control for gait generation and rough terrain mobility, and fault tolerance. The controller was implemented, debugged, and tested on Hannibal. Through a series of experiments, we examined Hannibal's gait generation, rough terrain locomotion, and fault tolerance performance. These results demonstrate that Hannibal exhibits robust, flexible, real-time locomotion over a variety of terrain and tolerates a multitude of hardware failures.

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Essery, RLH & JW, Pomeroy, (2004). Vegetation and topographic control of wind-blown snow distributions in distributed and aggregated simulations. Journal of Hydrometeorology, 5, 735-744.

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National Institute of Child Health and Human Development (HD051804)

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1) A large body of behavioral data conceming animal and human gaits and gait transitions is simulated as emergent properties of a central pattern generator (CPG) model. The CPG model incorporates neurons obeying Hodgkin-Huxley type dynamics that interact via an on-center off-surround anatomy whose excitatory signals operate on a faster time scale than their inhibitory signals. A descending cornmand or arousal signal called a GO signal activates the gaits and controL their transitions. The GO signal and the CPG model are compared with neural data from globus pallidus and spinal cord, among other brain structures. 2) Data from human bimanual finger coordination tasks are simulated in which anti-phase oscillations at low frequencies spontaneously switch to in-phase oscillations at high frequencies, in-phase oscillations can be performed both at low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, and a "seagull effect" of larger errors occurs at intermediate phases. When driven by environmental patterns with intermediate phase relationships, the model's output exhibits a tendency to slip toward purely in-phase and anti-phase relationships as observed in humans subjects. 3) Quadruped vertebrate gaits, including the amble, the walk, all three pairwise gaits (trot, pace, and gallop) and the pronk are simulated. Rapid gait transitions are simulated in the order--walk, trot, pace, and gallop--that occurs in the cat, along with the observed increase in oscillation frequency. 4) Precise control of quadruped gait switching is achieved in the model by using GO-dependent modulation of the model's inhibitory interactions. This generates a different functional connectivity in a single CPG at different arousal levels. Such task-specific modulation of functional connectivity in neural pattern generators has been experimentally reported in invertebrates. Phase-dependent modulation of reflex gain has been observed in cats. A role for state-dependent modulation is herein predicted to occur in vertebrates for precise control of phase transitions from one gait to another. 5) The primary human gaits (the walk and the run) and elephant gaits (the amble and the walk) are sirnulated. Although these two gaits are qualitatively different, they both have the same limb order and may exhibit oscillation frequencies that overlap. The CPG model simulates the walk and the run by generating oscillations which exhibit the same phase relationships. but qualitatively different waveform shapes, at different GO signal levels. The fraction of each cycle that activity is above threshold quantitatively distinguishes the two gaits, much as the duty cycles of the feet are longer in the walk than in the run. 6) A key model properly concerns the ability of a single model CPG, that obeys a fixed set of opponent processing equations to generate both in-phase and anti-phase oscillations at different arousal levels. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases.

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This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.

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This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-Integration-To-Endpoint (VITE) model suggests how synchronous multi-joint trajectories are generated and performed at variable speeds. The Factorization-of-LEngth-and-TEnsion (FLETE) model suggests how outflow movement commands from a VITE model may be performed at variable force levels without a loss of positional accuracy. The invariance of positional control under speed and force rescaling sheds new light upon a familiar strategy of motor skill development: Skill learning begins with performance at low speed and low limb compliance and proceeds to higher speeds and compliances. The VITE model helps to explain many neural and behavioral data about trajectory formation, including data about neural coding within the posterior parietal cortex, motor cortex, and globus pallidus, and behavioral properties such as Woodworth's Law, Fitts Law, peak acceleration as a function of movement amplitude and duration, isotonic arm movement properties before and after arm-deafferentation, central error correction properties of isometric contractions, motor priming without overt action, velocity amplification during target switching, velocity profile invariance across different movement distances, changes in velocity profile asymmetry across different movement durations, staggered onset times for controlling linear trajectories with synchronous offset times, changes in the ratio of maximum to average velocity during discrete versus serial movements, and shared properties of arm and speech articulator movements. The FLETE model provides new insights into how spina-muscular circuits process variable forces without a loss of positional control. These results explicate the size principle of motor neuron recruitment, descending co-contractive compliance signals, Renshaw cells, Ia interneurons, fast automatic reactive control by ascending feedback from muscle spindles, slow adaptive predictive control via cerebellar learning using muscle spindle error signals to train adaptive movement gains, fractured somatotopy in the opponent organization of cerebellar learning, adaptive compensation for variable moment-arms, and force feedback from Golgi tendon organs. More generally, the models provide a computational rationale for the use of nonspecific control signals in volitional control, or "acts of will", and of efference copies and opponent processing in both reactive and adaptive motor control tasks.

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An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing or visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greaterr persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence: due to adaptation with a stimulus of like orientation, an increase or persistence due to adaptation with a stimulus of perpendicular orientation, and an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

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Renal failure (RF) is associated with an over activation of the sympathetic nervous system. The aim of this thesis was to investigate the hypothesis that as the kidney progresses into RF there is an inappropriate and sustained activation of renal afferent nerves which results in a dysregulation of basal RSNA and reflexly controlled RSNA by the high and low pressure baroreceptors. Baroreflex gain curves for both RSNA and HR were generated in control and RF rats. This study clearly showed a blunted high-pressure baroreflex in RF rats, an impairment which was almost completely corrected by bilateral renal denervation. The integrity of the low-pressure cardiopulmonary receptors to inhibit RSNA was investigated using acute saline volume. Again, a blunted reflex sympatho-inhibition of RSNA was observed, which was corrected by renal denervation. Finally a functional study to examine how the renal excretory response to volume expansion differed in RF was carried out. This study revealed an impairment of the low-pressure baroreflex control of the sympathetic outflow. The result of these studies suggest that cisplatin induced RF initiates a neural signal from within the kidney, which over rides the normal reflex regulation of RSNA by the high and low – pressure baroreceptors and that this impairment in function can be normalised by renal denervation. This raises further questions as to the mechanisms involved in the afferent over activation arising from the diseased kidneys.

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The gut-hormone, ghrelin, activates the centrally expressed growth hormone secretagogue 1a (GHS-R1a) receptor, or ghrelin receptor. The ghrelin receptor is a G-protein coupled receptor (GPCR) expressed in several brain regions, including the arcuate nucleus (Arc), lateral hypothalamus (LH), ventral tegmental area (VTA), nucleus accumbens (NAcc) and amygdala. Activation of the GHS-R1a mediates a multitude of biological activities, including release of growth hormone and food intake. The ghrelin signalling system also plays a key role in the hedonic aspects of food intake and activates the dopaminergic mesolimbic circuit involved in reward signalling. Recently, ghrelin has been shown to be involved in mediating a stress response and to mediate stress-induced food reward behaviour via its interaction with the HPA-axis at the level of the anterior pituitary. Here, we focus on the role of the GHS-R1a receptor in reward behaviour, including the motivation to eat, its anxiogenic effects, and its role in impulsive behaviour. We investigate the functional selectivity and pharmacology of GHS-R1a receptor ligands as well as crosstalk of the GHS-R1a receptor with the serotonin 2C (5-HT2C) receptor, which represent another major target in the regulation of eating behaviour, stress-sensitivity and impulse control disorders. We demonstrate, to our knowledge for the first time, the direct impact of GHS-R1a signalling on impulsive responding in a 2-choice serial reaction time task (2CSRTT) and show a role for the 5-HT2C receptor in modulating amphetamine-associated impulsive action. Finally, we investigate differential gene expression patterns in the mesocorticolimbic pathway, specifically in the NAcc and PFC, between innate low- and high-impulsive rats. Together, these findings are poised to have important implications in the development of novel treatment strategies to combat eating disorders, including obesity and binge eating disorders as well as impulse control disorders, including, substance abuse and addiction, attention deficit hyperactivity disorder (ADHD) and mood disorders.

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The behaviour towards electron transfer of self-assembled monolayers of 2-mercaptobenzimidazole (MBI) and 2-mercaptobenzimidazole-5-sulfonate (MBIS) on Au(1 1 1) was examined by cyclic voltammetry. The influence of the monolayers was drastically dependent on the charge of the redox probe used. When [Ru(NH3)6]3+ is used, a post-adsorption peak characteristic of the adsorption of the redox probe is detected only at the MBIS modified electrode. Taking advantage of this difference, ac voltammetry has been used to determine the surface composition when mixed monolayers are formed by immersion of the gold substrate in mixtures of different molar fractions of MBI and MBIS. Results clearly indicate that the ionic strength of the immersion solution plays a key role in the surface composition when a charged surfactant is mixed with non-charged surfactant. © 2006 Elsevier B.V. All rights reserved.

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"Push-pull" chromophores based on extended pi-electron systems have been designed to exhibit exceptionally large molecular hyperpolarizabilities. We have engineered an amphiphilic four-helix bundle peptide to vectorially incorporate such hyperpolarizable chromophores having a metalloporphyrin moiety, with high specificity into the interior core of the bundle. The amphiphilic exterior of the bundle facilitates the formation of densely packed monolayer ensembles of the vectorially oriented peptide-chromophore complexes at the liquid-gas interface. Chemical specificity designed into the ends of the bundle facilitates the subsequent covalent attachment of these monolayer ensembles onto the surface of an inorganic substrate. In this article, we describe the structural characterization of these monolayer ensembles at each stage of their fabrication for one such peptide-chromophore complex designated as AP0-RuPZn. In the accompanying article, we describe the characterization of their macroscopic nonlinear optical properties.

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To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.

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Before fertilization, vertebrate eggs are arrested in meiosis II by cytostatic factor (CSF), which holds the anaphase-promoting complex (APC) in an inactive state. It was recently reported that Mos, an integral component of CSF, acts in part by promoting the Rsk-mediated phosphorylation of the APC inhibitor Emi2/Erp1. We report here that Rsk phosphorylation of Emi2 promotes its interaction with the protein phosphatase PP2A. Emi2 residues adjacent to the Rsk phosphorylation site were important for PP2A binding. An Emi2 mutant that retained Rsk phosphorylation but lacked PP2A binding could not be modulated by Mos. PP2A bound to Emi2 acted on two distinct clusters of sites phosphorylated by Cdc2, one responsible for modulating its stability during CSF arrest and one that controls binding to the APC. These findings provide a molecular mechanism for Mos action in promoting CSF arrest and also define an unusual mechanism, whereby protein phosphorylation recruits a phosphatase for dephosphorylation of distinct sites phosphorylated by another kinase.