43 resultados para Control applications


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This research details methods to improve upon current worst-case message response time analysis of CAN networks. Also, through the development of a CAN network model, and using modern simulation software, methods were shown to provide more realistic analyses of both sporadic and periodic messages on CAN networks prior to implementation.

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Locusts and grasshoppers cause considerable economic damage to agriculture worldwide. The Australian Plague Locust Commission uses multiple pesticides to control locusts in eastern Australia. Avian exposure to agricultural pesticides is of conservation concern, especially in the case of rare and threatened species. The aim of this study was to evaluate the probability of pesticide exposure of native avian species during operational locust control based on knowledge of species occurrence in areas and times of application. Using presence-absence data provided by the Birds Australia Atlas for 1998 to 2002, we developed a series of generalized linear models to predict avian occurrences on a monthly basis in 0.5 degrees grid cells for 280 species over 2 million km2 in eastern Australia. We constructed species-specific models relating occupancy patterns to survey date and location, rainfall, and derived habitat preference. Model complexity depended on the number of observations available. Model output was the probability of occurrence for each species at times and locations of past locust control operations within the 5-year study period. Given the high spatiotemporal variability of locust control events, the variability in predicted bird species presence was high, with 108 of the total 280 species being included at least once in the top 20 predicted species for individual space-time events. The models were evaluated using field surveys collected between 2000 and 2005, at sites with and without locust outbreaks. Model strength varied among species. Some species were under- or over-predicted as times and locations of interest typically did not correspond to those in the prediction data set and certain species were likely attracted to locusts as a food source. Field surveys demonstrated the utility of the spatially explicit species lists derived from the models but also identified the presence of a number of previously unanticipated species. These results also emphasize the need for special consideration of rare and threatened species that are poorly predicted by presence-absence models. This modeling exercise was a useful a priori approach in species risk assessments to identify species present at times and locations of locust control applications, and to discover gaps in our knowledge and need for further focused data collection.

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Prediction interval (PI) has been extensively used to predict the forecasts for nonlinear systems as PI-based forecast is superior over point-forecast to quantify the uncertainties and disturbances associated with the real processes. In addition, PIs bear more information than point-forecasts, such as forecast accuracy. The aim of this paper is to integrate the concept of informative PIs in the control applications to improve the tracking performance of the nonlinear controllers. In the present work, a PI-based controller (PIC) is proposed to control the nonlinear processes. Neural network (NN) inverse model is used as a controller in the proposed method. Firstly, a PI-based model is developed to construct PIs for every sample or time instance. The PIs are then fed to the NN inverse model along with other effective process inputs and outputs. The PI-based NN inverse model predicts the plant input to get the desired plant output. The performance of the proposed PIC controller is examined for a nonlinear process. Simulation results indicate that the tracking performance of the PIC is highly acceptable and better than the traditional NN inverse model-based controller.

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In many quality control applications the quality of process or product is characterized and summarized by a relation (profile) between a response variable and one or more explanatory variables. Such profiles can be modeled using linear or nonlinear regression models. In this paper we use artificial neural networks to detect and classify the shifts in linear profiles. Three monitoring methods based on artificial neural networks are developed to monitor linear profiles. Their efficacies are assessed using average run length criterion. © 2010 Elsevier Ltd. All rights reserved.

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This paper introduces an aggregation algorithm for airborne swarming guided weapon systems, which can aggregate munitions into a given shape while reaching the surface. The algorithm uses an artificial force based controller to navigate the members of the swarm into the desired geographical position and evenly distribute them inside the shape. Inter-member repulsion forces are used to avoid collisions among members, which is crucial for a weapon deployment system. Moreover, a lower bound for the release height was obtained which guarantee convergence of the complete weapon system into the target area. The proposed swarming guided weapon system was tested using computer simulations.

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The Orange River, South Africa’s largest river, is a critical water resource for the country. In spite of the clear economic benefits of regulating river flows through a series of impoundments, one of the significant undesirable ecological consequences of this regulation has been the regular outbreaks of the pest blackfly species Simulium chutteri and S. damnosum s.l. (Diptera: Simuliidae). The current control programme, carried out by the South African National Department of Agriculture, uses regular applications, by helicopter, of the target-specific bacterial larvicide Bacillus thuringiensis var. israelensis. While cost-benefit analyses show significant benefits to the control programme, benefits could potentially be further increased through applying smaller volumes of larvicide in an optimised manner, which incorporates upstream residual amounts of pesticide through downstream carry. Using an optimisation technique applied in the West African Onchocerciasis Control Programme, to a 136 km stretch of the Orange River which includes 31 blackfly breeding sites, we demonstrate that 28.5% less larvicide could be used to potentially achieve the same control of blackfly. This translates into potential annual savings of between R540 000 and R1 800 000. A comparison of larvicide volumes estimated using traditional vs. optimised approaches at different discharges, illustrates that the savings on optimisation decline linearly with increasing flow volumes. Larvicide applications at the lowest discharge considered (40 m3·s-1) showed the greatest benefits from optimisations, with benefits remaining but decreasing to a theoretical 30% up to median flows of 100 m3·s-1. Given that almost 70% of flows in July are less than 100 m3·s-1, we suggest that an optimised approach is appropriate for the Orange River Blackfly Control Programme, particularly for flow volumes of less than 100 m3·s-1. We recommend that trials be undertaken over two reaches of the Orange River, one using the traditional approach, and another using the optimised approach, to test the efficacy of using optimised volumes of B.t.i.

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Giving robots the ability to autonomously move around in various real-world environments has been a major goal of AI (artificial intelligence) for quite some time. To this end it is vital for robots to be able to perceive their surroundings in 3D; they must be able to estimate the range of obstacles in their path.

Animals navigate through various uncontrolled environments with seemingly little effort. Flying insects, especially, are quite adept at manoeuvring in complex, unpredictable and possibly hostile and hazardous environments.

In this paper it is shown that very simple motion cues, inspired by the visual navigation of flying insects, can be used to provide a mobile robot with the ability to successfully traverse a corridor environment. Equipping an autonomous mobile robot with the ability to successfully navigate real-word environments (in real-time) constitutes a major challenge for AI and robotics. It is in this area that insect based navigation has something to offer.

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In this paper, a hybrid DC microgrid consisting of a diesel generator with a rectifier, a solar photovoltaic (PV) system, and a battery energy storage system is presented in relation to an effective power management strategy and different control techniques are adopted to power electronic interfaces. The solar PV and battery energy storage systems are considered as the main sources of energy sources that supply the load demand on a daily basis whereas the diesel generator is used as a backup for the emergency operation of the microgrid. All system components are connected to a common DC bus through an appropriate power electronics devices (e.g., rectifier systems, DC/DC converter). Also a detailed sizing philosophy of all components along with the energy management strategy is proposed. Energy distribution pattern of each individual component has been conducted based on the monthly basis along with a power management algorithm. The power delivered by the solar PV system and diesel generator is controlled via DC-DC converterand excitation controllers which are designed based on a linearquadratic regulator (LQR) technique as as proportional integral (PI)controllers. The component level power distribution is investigatedusing these controllers under fluctuating load and solar irradiationconditions and comparative results are presented.

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This paper reports a case study of end-user control in delivery of Web-based electronic services. The case study concentrates the adoption of a Web-based electronic system being implemented in processing student’s admission applications on a Web site. The end-user’s control interface provides information on the detail existing in the Web-based electronic service. This insight into end-user synthesis in developing effective control in Web service environment relates to ease of use in doing the task. To assume the leverage of end-user control strictly on the basis of the Web service usage would limit the purpose of understanding. Rather it is suggested that it would be better to develop an approach to study the end-user ease of use interface in doing the task with the user’s perception towards Web-based interactivity.

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Parallel file systems offer improved performance over traditional file systems by allowing processes to access file data, stored over a number of disks, in parallel. When this file is to be accessed by many processes at the same time for reading and writing, the problem of maintaining file consistency is introduced. The general approach to maintaining file consistency is through the use locks which grant a single process exclusive access to the file. Existing studies have found parallel file systems and associated applications rarely experience conflict, resulting in unnecessary overheads from locks being acquired. This paper examines an alternate approach to maintaining file consistency, which is based on optimistic concurrency control. This approach was shown to have a much smaller overhead when compared with traditional lock-based approaches; especially in situations when there is little contention. This paper presents the design, implementation and initial testing results of an optimistic based concurrency control mechanism.

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Reverse osmosis (RO) membranes can be used to treat ground water, surface water and wastewater, but a major problem in RO membrane applications is fouling. Many studies have investigated the mechanisms of fouling in RO membranes and suggested various methods to control the membrane fouling. This paper reviews several aspects of RO membranes, such as the types of membrane fouling, their effects on RO membrane processes and fouling control technologies, focussed on the appropriate feed pretreatment technologies and cleaning methods, especially on the membrane filtration pretreatment processes, including microfiltration (MF), ultrafiltration (UF) and nanofiltration (NF), which are the new trends in designing a pretreatment system in the application of RO.

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The objective of this research is to model and analyze candidate hull configurations for a low-cost, modular, autonomous underwater robot. As the computational power and speed of microprocessors continue to progress, we are seeing a growth in the research, development, and the utilization of underwater robots. The number of applications is broadening in the R&D and science communities, especially in the area of multiple, collaborative robots. These underwater collaborative robots represent an instantiation of a System of Systems (SoS). While each new researcher explores a unique application, control method, etc. a new underwater robot vehicle is designed, developed, and deployed. This sometimes leads to one-off designs that are costly. One limit to the wide-scale utilization of underwater robotics is the cost of development. Another limit is the ability to modify the configuration for new applications and evolving requirements. Consequently, we are exploring autonomous underwater vehicle (AUV) hull designs towards the goal of modularity, vehicle dexterity, and minimizing the cost. In our analysis, we have employed 3D solid modeling tools and finite element methods. In this paper we present our initial results and discuss ongoing work.

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Haptic human-machine interfaces and similar techniques to enhancing human-robotic interaction offer significant potential over conventional approaches. This work considers achieving intuitive motion control of a tracked mobile robotic platform utilising a 3D virtual haptic cone. The 3D haptic cone extends upon existing approaches by introducing of a third dimension to the haptic control surface. It is suggested that this approach improves upon existing methods by providing the human operator with an intuitive method for issuing vehicle motion commands whilst still facilitating simultaneous real-time haptic augmentation regarding the task at hand. The presented approach is considered in the context of mobile robotic teleoperation however offers potential across many applications. Using the 2D haptic control surface as a benchmark, preliminary evaluation of the 3D haptic cone approach demonstrates a significant improvement in the ability to command the robot to cease motion.

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Haptic human-machine interfaces and similar techniques to enhancing human-robotic interaction offer significant potential over conventional approaches. This work considers achieving intuitive motion control of a tracked mobile robotic platform utilising a 3D virtual haptic cone. The 3D haptic cone extends upon existing approaches by introducing of a third dimension to the haptic control surface. It is suggested that this approach improves upon existing methods by providing the human operator with an intuitive method for issuing vehicle motion commands whilst still facilitating simultaneous real-time haptic augmentation regarding the task at hand. The presented approach is considered in the context of mobile robotic teleoperation however offers potential across many applications. Using the 2D haptic control surface as a benchmark, preliminary evaluation of the 3D haptic cone approach demonstrates a significant improvement in the ability to command the robot to cease motion.