303 resultados para Unmanned Airborne Vehicles
Resumo:
A series of flooding events occurred in Queensland, Australia during December 2010 and January 2011. The state’s capital city of Brisbane experienced major flooding in January 2011, when the Brisbane River broke its bank and inundated low lying areas.
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Vehicle emissions are a significant source of fine particles (Dp < 2.5 µm) in an urban environment. These fine particles have been shown to have detrimental health effects, with children thought to be more susceptible. Vehicle emissions are mainly carbonaceous in nature, and carbonaceous aerosols can be defined as either elemental carbon (EC) or organic carbon (OC). EC is a soot-like material emitted from primary sources while OC fraction is a complex mixture of hundreds of organic compounds from either primary or secondary sources (Cao et al., 2006). Therefore the ratio of OC/EC can aid in the identification of source. The purpose of this paper is to use the concentration of OC and EC in fine particles to determine the levels of vehicle emissions in schools. It is expected that this will improve the understanding of the potential exposure of children in a school environment to vehicle emissions.
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The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup
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The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.
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Debugging control software for Micro Aerial Vehicles (MAV) can be risky out of the simulator, especially with professional drones that might harm people around or result in a high bill after a crash. We have designed a framework that enables a software application to communicate with multiple MAVs from a single unified interface. In this way, visual controllers can be first tested on a low-cost harmless MAV and, after safety is guaranteed, they can be moved to the production MAV at no additional cost. The framework is based on a distributed architecture over a network. This allows multiple configurations, like drone swarms or parallel processing of drones' video streams. Live tests have been performed and the results show comparatively low additional communication delays, while adding new functionalities and flexibility. This implementation is open-source and can be downloaded from github.com/uavster/mavwork
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This paper presents a method for investigating ship emissions, the plume capture and analysis system (PCAS), and its application in measuring airborne pollutant emission factors (EFs) and particle size distributions. The current investigation was conducted in situ, aboard two dredgers (Amity: a cutter suction dredger and Brisbane: a hopper suction dredger) but the PCAS is also capable of performing such measurements remotely at a distant point within the plume. EFs were measured relative to the fuel consumption using the fuel combustion derived plume CO2. All plume measurements were corrected by subtracting background concentrations sampled regularly from upwind of the stacks. Each measurement typically took 6 minutes to complete and during one day, 40 to 50 measurements were possible. The relationship between the EFs and plume sample dilution was examined to determine the plume dilution range over which the technique could deliver consistent results when measuring EFs for particle number (PN), NOx, SO2, and PM2.5 within a targeted dilution factor range of 50-1000 suitable for remote sampling. The EFs for NOx, SO2, and PM2.5 were found to be independent of dilution, for dilution factors within that range. The EF measurement for PN was corrected for coagulation losses by applying a time dependant particle loss correction to the particle number concentration data. For the Amity, the EF ranges were PN: 2.2 - 9.6 × 1015 (kg-fuel)-1; NOx: 35-72 g(NO2).(kg-fuel)-1, SO2 0.6 - 1.1 g(SO2).(kg-fuel)-1and PM2.5: 0.7 – 6.1 g(PM2.5).(kg-fuel)-1. For the Brisbane they were PN: 1.0 – 1.5 x 1016 (kg-fuel)-1, NOx: 3.4 – 8.0 g(NO2).(kg-fuel)-1, SO2: 1.3 – 1.7 g(SO2).(kg-fuel)-1 and PM2.5: 1.2 – 5.6 g(PM2.5).(kg-fuel)-1. The results are discussed in terms of the operating conditions of the vessels’ engines. Particle number emission factors as a function of size as well as the count median diameter (CMD), and geometric standard deviation of the size distributions are provided. The size distributions were found to be consistently uni-modal in the range below 500 nm, and this mode was within the accumulation mode range for both vessels. The representative CMDs for the various activities performed by the dredgers ranged from 94-131 nm in the case of the Amity, and 58-80 nm for the Brisbane. A strong inverse relationship between CMD and EF(PN) was observed.
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Emission rates of ammonia (NH3) are reported for a fleet of 130 light-, medium-, and heavy-duty vehicles recruited in Guangzhou, China. NH3 measurements were performed using Nessler's Reagents spectrophotometry and nationwide standard chassis dynamometer test cycles required by Chinese EPA. Emissions of CO and NOx were also measured during these test cycles. Emission factors of NH3 were calculated for each type of vehicle and used to estimate the total emissions of NH3 from motor vehicles in Guangzhou (GZ) in 2009. Emission factors of NH3 show large variations among different categories of vehicles, with a range from 4 to 138 mg km-1. The average emissions of NH3 in Guangzhou in 2009 were estimated to be 983 t, with a range from 373 to 2136 t. In addition, it was found that vehicles with the highest NH3 emission rates possess the following characteristics: mediumand heavy-duty vehicles, certified with out-of-date emission standards, mid-range odometer readings, and higher CO and NOx emission rates. The results of this study will be useful for developing NH3 emissions inventories in Guangzhou and other urban areas in China.
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This work presents a collision avoidance approach based on omnidirectional cameras that does not require the estimation of range between two platforms to resolve a collision encounter. Our method achieves minimum separation between the two vehicles involved by maximising the view-angle given by the omnidirectional sensor. Only visual information is used to achieve avoidance under a bearing- only visual servoing approach. We provide theoretical problem formulation, as well as results from real flights using small quadrotors
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This paper outlines an innovative and feasible flight control scheme for a rotary-wing unmanned aerial system (RUAS) with guaranteed safety and reliable flight quality in a gusty environment. The proposed control methodology aims to increase gust-attenuation capability of a RUAS to ensure improved flight performance when strong gusts occur. Based on the design of an effective estimator, an altitude controller is firstly constructed to synchronously compensate for fluctuations of the main rotor thrust which might lead to crashes in a gusty environment. Afterwards, a nonlinear state feedback controller is proposed to stabilize horizontal positions of the RUAS with gust-attenuation property. Performance of the proposed control framework is evaluated using parameters of a Vario XLC helicopter and high-fidelity simulations show that the proposed controllers can effectively reduce side-effect of gusts and demonstrate performance improvement when compared with the proportional-integral-derivative (PID) controllers.
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This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.
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Air pollution is a widespread health problem associated with respiratory symptoms. Continuous exposure monitoring was performed to estimate alveolar and tracheobronchial dose, measured as deposited surface area, for 103 children and to evaluate the long-term effects of exposure to airborne particles through spirometry, skin prick tests and measurement of exhaled nitric oxide (eNO). The mean daily alveolar deposited surface area dose received by children was 1.35×103 mm2. The lowest and highest particle number concentrations were found during sleeping and eating time. A significant negative association was found between changes in pulmonary function tests and individual dose estimates. Significant differences were found for asthmatics, children with allergic rhinitis and sensitive to allergens compared to healthy subjects for eNO. Variation is a child’s activity over time appeared to have a strong impact on respiratory outcomes, which indicates that personal monitoring is vital for assessing the expected health effects of exposure to particles.
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KEEP CLEAR pavement markings are widely used at urban signalised intersections to indicate to drivers to avoid entering blocked intersections. For example, ‘Box junctions’ are most widely used in the United Kingdom and other European countries. However, in Australia, KEEP CLEAR markings are mostly used to improve access from side roads onto a main road, especially when the side road is very close to a signalised intersection. This paper aims to reveal how the KEEP CLEAR markings affect the dynamic performance of the queuing vehicles on the main road, where the side road access is near a signalised intersection. Raw traffic field data was collected from an intersection at the Gold Coast, Australia, and the Kanade–Lucas–Tomasi (KLT) feature tracker approach was used to extract dynamic vehicle data from the raw video footage. The data analysis reveals that the KEEP CLEAR markings generate positive effects on the queuing vehicles in discharge on the main road. This finding refutes the traditional viewpoint that the KEEP CLEAR pavement markings will cause delay for the queuing vehicles’ departure due to the enlarged queue spacing. Further studies are suggested in this paper as well.
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This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.
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Plug-in electric vehicles (PEVs) are increasingly popular in the global trend of energy saving and environmental protection. However, the uncoordinated charging of numerous PEVs can produce significant negative impacts on the secure and economic operation of the power system concerned. In this context, a hierarchical decomposition approach is presented to coordinate the charging/discharging behaviors of PEVs. The major objective of the upper-level model is to minimize the total cost of system operation by jointly dispatching generators and electric vehicle aggregators (EVAs). On the other hand, the lower-level model aims at strictly following the dispatching instructions from the upper-level decision-maker by designing appropriate charging/discharging strategies for each individual PEV in a specified dispatching period. Two highly efficient commercial solvers, namely AMPL/IPOPT and AMPL/CPLEX, respectively, are used to solve the developed hierarchical decomposition model. Finally, a modified IEEE 118-bus testing system including 6 EVAs is employed to demonstrate the performance of the developed model and method.
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As a good solution to the shortage and environmental unfriendliness of fossil fuels, plug-in electric vehicles (PEVs) attract much interests of the public. To investigate the problems caused by the integration of numerous PEVs, a lot of research work has been done on the grid impacts of PEVs in aspects including thermal loading, voltage regulation, transformer loss of life, unbalance, losses, and harmonic distortion levels. This paper surveys the-state-of-the-art of the research in this area and outline three possible measures for a power grid company to make full use of PEVs.