822 resultados para Event-based control


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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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M J Neal and J Timmis. Timidity: A useful mechanism for robot control? Informatica - special issue on perception and emotion based control, 4(27):197-204, 2003.

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In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs objective information about the trauma and peritraumatic emotions but uses retrospective memory reports that can have substantial biases. Negative events and emotions that do not satisfy the current diagnostic criteria for a trauma can be followed by symptoms that would otherwise qualify for PTSD. Predisposing factors that affect the current memory have large effects on symptoms. The inability-to-recall-an-important-aspect-of-the-trauma symptom does not correlate with other symptoms. Loss or enhancement of the trauma memory affects PTSD symptoms in predictable ways. Special mechanisms that apply only to traumatic memories are not needed, increasing parsimony and the knowledge that can be applied to understanding PTSD.

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This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed. (c) 2004 Elsevier Ltd. All rights reserved.

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This paper exposes the strengths and weaknesses of the recently proposed velocity-based local model (LM) network. The global dynamics of the velocity-based blended representation are directly related to the dynamics of the underlying local models, an important property in the design of local controller networks. Furthermore, the sub-models are continuous-time and linear providing continuity with established linear theory and methods. This is not true for the conventional LM framework, where the global dynamics are only weakly related to the affine sub-models. In this paper, a velocity-based multiple model network is identified for a highly nonlinear dynamical system. The results show excellent dynamical modelling performances, highlighting the value of the velocity-based approach for the design and analysis of LM based control. Three important practical issues are also addressed. These relate to the blending of the velocity-based local models, the use of normalised Gaussian basis functions and the requirement of an input derivative.

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The prevailing paradigm for researching sensorimotor synchronisation in humans involves finger tapping and temporal accuracy measures. However, many successful sensorimotor synchronisation actions require not only to be 'in time', but also to be in a predefined spatial position. Reaching this spatial position in many everyday actions often exceeds the average amplitude of a finger movement. The aim of this study is to address how people coordinate their movement to be in the right place at the right time when the scale of the movement varies. Does the scale of the movement and accuracy demands of the movement change the ability to accurately synchronise? To address these questions, a sensorimotor synchronisation task with three different inter-beat intervals, two different movement amplitudes and two different target widths was used. Our experiment demonstrated that people use different timing strategies-employing either a movement strategy (varying movement time) or a waiting strategy (keeping movement time constant) for large-scale movements. Those two strategies were found to be equally successful in terms of temporal accuracy and variability (spread of errors). With longer interval durations (2.5 and 3.5 s), variability of sensorimotor synchronisation performance increased (measured as the spread of errors). Analysing the data using the Vorberg and Wing (Handbook of perception and action. Academic Press, New York, pp 181-262, 1996) model shows a need to develop further existing timing models of sensorimotor synchronisation so that they could apply to large-scale movements, where different movement strategies naturally emerge.

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This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks’ QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network
management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the
prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.

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Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

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There is lack of consistent evidence as to how well PD patients are able to accurately time their movements across space with an external acoustic signal. For years, research based on the finger-tapping paradigm, the most popular paradigm for exploring the brain's ability to time movement, has provided strong evidence that patients are not able to accurately reproduce an isochronous interval [i.e., Ref. (1)]. This was undermined by Spencer and Ivry (2) who suggested a specific deficit in temporal control linked to emergent, rhythmical movement not event-based actions, which primarily involve the cerebellum. In this study, we investigated motor timing of seven idiopathic PD participants in event-based sensorimotor synchronization task. Participants were asked to move their finger horizontally between two predefined target zones to synchronize with the occurrence of two sound events at two time intervals (1.5 and 2.5 s). The width of the targets and the distance between them were manipulated to investigate impact of accuracy demands and movement amplitude on timing performance. The results showed that participants with PD demonstrated specific difficulties when trying to accurately synchronize their movements to a beat. The extent to which their ability to synchronize movement was compromised was found to be related to the severity of PD, but independent of the spatial constraints of the task.

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Salespeople play a pivotal role in promoting new products. Therefore, managers need to know what control mechanism (i.e., output-based control, behavior-based control, or knowledge-based control) can improve their salespeople's new product sales performance. Furthermore, managers may be able to assist salespeople in performing better by having a strong market orientation. The literature has been inconsistent regarding the effects of sales management control mechanisms and has not yet incorporated market orientation into a sales management control framework. The current study surveyed 315 Taiwanese salespeople from publicly traded electronics companies with the aim of contributing to the sales management literature. The results show that sales management controls can directly affect salespeople's innovativeness, which, in turn, affects new product sales performance. However, sales management controls cannot affect performance directly. Furthermore, market orientation can positively moderate the relationship between salespeople's innovativeness and new product sales performance.

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This paper deals with the problem of stabilizing a class of structures subject to an uncertain excitation due to the temporary coupling of the main system with another uncertain dynamical subsystem. A Lyapunov function based control scheme is proposed to attenuate the structural vibration. In the control design, the actuator dynamics is taken into account. The control scheme is implemented by using only feedback information of the main system. The effectiveness of the control scheme is shown for a bridge platform with crossing vehicle

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Control systems theory can be a discipline difficult to learn without some laboratory help. With the help of focused laboratories this discipline turns to be very interesting to the students involved. The main problem is that laboratories aren't always available to students, and sometimes, when they are available, aren't big enough to a growing student population. Thus, with computer networks growing so fast, why don't create remote control labs that can be used by a large number of students? Why don't create remote control labs using Internetⓒ Copyright ?2001 IFAC Keywords: Remote Control, Computer Networks, Database, Educational Aids, Laboratory Education, Communication Control Applications.

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Left inferior frontal gyrus (IFG) is a critical neural substrate for the resolution of proactive interference (PI) in working memory. We hypothesized that left IFG achieves this by controlling the influence of familiarity- versus recollection-based information about memory probes. Consistent with this idea, we observed evidence for an early (200 msec)-peaking signal corresponding to memory probe familiarity and a late (500 msec)-resolving signal corresponding to full accrual of trial-related contextual ("recollection-based") information. Next, we applied brief trains of repetitive transcranial magnetic stimulation (rTMS) time locked to these mnemonic signals, to left IFG and to a control region. Only early rTMS of left IFG produced a modulation of the false alarm rate for high-PI probes. Additionally, the magnitude of this effect was predicted by individual differences in susceptibility to PI. These results suggest that left IFG-based control may bias the influence of familiarity- and recollection-based signals on recognition decisions.