940 resultados para neural-control


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In the rate-based flow control for ATM Available Bit Rate service, fairness is an important requirement, i.e. each flow should be allocated a fair share of the available bandwidth in the network. Max–min fairness, which is widely adopted in ATM, is appropriate only when the minimum cell rates (MCRs) of the flows are zero or neglected. Generalised max–min (GMM) fairness extends the principle of the max–min fairness to accommodate MCR. In this paper, we will discuss the formulation of the GMM fair rate allocation, propose a centralised algorithm, analyse its bottleneck structure and develop an efficient distributed explicit rate allocation algorithm to achieve the GMM fairness in an ATM network. The study in this paper addresses certain theoretical and practical issues of the GMM fair rate allocation.

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In this paper, a rate-based flow control scheme based upon per-VC virtual queuing is proposed for the Available Bit Rate (ABR) service in ATM. In this scheme, each VC in a shared buffer is assigned a virtual queue, which is a counter. To achieve a specific kind of fairness, an appropriate scheduler is applied to the virtual queues. Each VC's bottleneck rate (fair share) is derived from its virtual cell departure rate. This approach of deriving a VC's fair share is simple and accurate. By controlling each VC with respect to its virtual queue and queue build-up in the shared buffer, network congestion is avoided. The principle of the control scheme is first illustrated by max–min flow control, which is realised by scheduling the virtual queues in round-robin. Further application of the control scheme is demonstrated with the achievement of weighted fairness through weighted round robin scheduling. Simulation results show that with a simple computation, the proposed scheme achieves the desired fairness exactly and controls network congestion effectively.

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This chapter outlines: a brief history of Australian Aboriginal health and health policy and then moves on to demonstrate how the Victorian Aboriginal Community Controlled Health Organisation (VACCHO) undertakes its work and is an example of 'decolonizing policy in action'. Moreover, it highlights how Aboriginal participation in the development of policy and in the planning, delivery, management and evaluation of health programs enables policies and programs to respond effectively to the needs of Aboriginal people and to change future health outcomes for them. It showcases how Aboriginal decision-making has gone some way to decolonizing policymaking and has addressed the power imbalance - both of which have been critical in the improvement in Aboriginal health outcomes.

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A high performance, low computational complexity rate-based flow control algorithm which can avoid congestion and achieve fairness is important to ATM available bit rate service. The explicit rate allocation algorithm proposed by Kalampoukas et al. is designed to achieve max–min fairness in ATM networks. It has several attractive features, such as a fixed computational complexity of O(1) and the guaranteed convergence to max–min fairness. In this paper, certain drawbacks of the algorithm, such as the severe overload of an outgoing link during transient period and the non-conforming use of the current cell rate field in a resource management cell, have been identified and analysed; a new algorithm which overcomes these drawbacks is proposed. The proposed algorithm simplifies the rate computation as well. Compared with Kalampoukas's algorithm, it has better performance in terms of congestion avoidance and smoothness of rate allocation.

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Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

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This correspondence paper addresses the problem of output feedback stabilization of control systems in networked environments with quality-of-service (QoS) constraints. The problem is investigated in discrete-time state space using Lyapunov’s stability theory and the linear inequality matrix technique. A new discrete-time modeling approach is developed to describe a networked control system (NCS) with parameter uncertainties and nonideal network QoS. It integrates a network-induced delay, packet dropout, and other network behaviors into a unified framework. With this modeling, an improved stability condition, which is dependent on the lower and upper bounds of the equivalent network-induced delay, is established for the NCS with norm-bounded parameter uncertainties. It is further extended for the output feedback stabilization of the NCS with nonideal QoS. Numerical examples are given to demonstrate the main results of the theoretical development.

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This paper presents a Genetic Algorithms (GA) approach to resolve traffic conflicts at a railway junction. The formulation of the problem for the suitable application of GA will be discussed and three neighborhoods have been proposed for generation evolution. The performance of the GA is evaluated by computer simulation. This study paves the way for more applications of artificial intelligence techniques on a rather conservative industry.

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In this paper, we present the design and construction of a prototype target tracking system. The experimental set up consists of three main modules for moving the object, detecting the motion of the object and its tracking. The mechanism for moving the object includes an object and two stepper motors and their driving and control circuitry. The detection of the object’s motion is realized by photo switch array. The tracking mechanism consists of a laser beam and two DC servomotors and their associated circuitry. The control algorithm is a standard fuzzy logic controller. The system is designed to operate in two modes in such a way that the role of target and tracker can be interchanged. Experimental results indicate that the fuzzy controller is capable of controlling the system in both modes.

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This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.

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Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

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This paper describes a thorough thermal study on a fleet of DC traction motors which were found to suffer from overheating after 3 years of full operation. Overheating of these traction motors is attributed partly because of the higher than expected number of starts and stops between train terminals. Another probable cause of overheating is the design of the traction motor and/or its control strategy. According to the motor manufacturer, a current shunt is permanently connected across the motor field winding. Hence, some of the armature current is bypassed into the current shunt. The motor then runs above its rated speed in the field weakening mode. In this study, a finite difference model has been developed to simulate the temperature profile at different parts inside the traction motor. In order to validate the simulation result, an empty vehicle loaded with drums of water was also used to simulate the full pay-load of a light rail vehicle experimentally. The authors report that the simulation results agree reasonably well with experimental data, and it is likely that the armature of the traction motor will run cooler if its field shunt is disconnected at low speeds

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A key feature in future aircraft operations will be automation of various aircraft processes, such as air traffic separation management and the management of forced landing events. Automated versions of these processes will often involve consideration of multiple modes of operations and hence require consideration of automated decision processes able to switch between various available modes of operations. This paper proposes a switching algorithm on the basis of max-min decision theory. This algorithm is particularly suitable in situations where each operational mode has access to different set of partial information. We apply our proposed algorithm to the air traffic separation management problem. A simulation study is presented that illustrates the performance of the proposed switching algorithm.

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Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

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Changes in stride characteristics and gait rhythmicity characterize gait in Parkinson's disease and are widely believed to contribute to falls in this population. However, few studies have examined gait in PD patients who fall. This study reports on the complexities of walking in PD patients who reported falling during a 12-month follow-up. Forty-nine patients clinically diagnosed with idiopathic PD and 34 controls had their gait assessed using three-dimensional motion analysis. Of the PD patients, 32 (65%) reported at least one fall during the follow-up compared with 17 (50%) controls. The results showed that PD patients had increased stride timing variability, reduced arm swing and walked with a more stooped posture than controls. Additionally, PD fallers took shorter strides, walked slower, spent more time in double-support, had poorer gait stability ratios and did not project their center of mass as far forward of their base of support when compared with controls. These stride changes were accompanied by a reduced range of angular motion for the hip and knee joints. Relative to walking velocity, PD fallers had increased mediolateral head motion compared with PD nonfallers and controls. Therefore, head motion could exceed “normal” limits, if patients increased their walking speed to match healthy individuals. This could be a limiting factor for improving gait in PD and emphasizes the importance of clinically assessing gait to facilitate the early identification of PD patients with a higher risk of falling.

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In this paper, two different high bandwidth converter control strategies are discussed. One of the strategies is for voltage control and the other is for current control. The converter, in each of the cases, is equipped with an output passive filter. For the voltage controller, the converter is equipped with an LC filter, while an output has an LCL filter for current controller. The important aspect that has been discussed the paper is to avoid computation of unnecessary references using high-pass filters in the feedback loop. The stability of the overall system, including the high-pass filters, has been analyzed. The choice of filter parameters is crucial for achieving desirable system performance. In this paper, the bandwidth of achievable performance is presented through frequency (Bode) plot of the system gains. It has been illustrated that the proposed controllers are capable of tracking fundamental frequency components along with low-order harmonic components. Extensive simulation results are presented to validate the control concepts presented in the paper.