869 resultados para Multi-vehicle control


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Some minerals are colloidal and are poorly diffracting . Vibrational spectroscopy offers one of the few methods for the assessment of the structure of these types of minerals. Among this group of minerals is zykaite with formula Fe4(AsO4)(SO4)(OH)•15H2O. The objective of this research is to determine the molecular structure of the mineral zykaite using vibrational spectroscopy. Raman and infrared bands are attributed to the AsO43-, SO42- and water stretching vibrations. The sharp band at 3515 cm-1 is assigned to the stretching vibration of the OH units. This mineral offers a mechanism for the formation of more crystalline minerals such as scorodite and bukovskyite. Arsenate ions can be removed from aqueous systems through the addition of ferric compounds such as ferric chloride. This results in the formation of minerals such as zykaite and pitticite (Fe3+,AsO4,SO4,H2O).

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The mineral arsentsumebite Pb2Cu(AsO4)(SO4)(OH), a copper arsenate-sulfate hydroxide of the brackebuschite group has been characterised by Raman spectroscopy. The brackebuschite mineral group are a series of monoclinic arsenates, phosphates and vanadates of the general formula A2B(XO4)(OH,H2O), where A may be Ba, Ca, Pb, Sr, while B may be Al, Cu2+,Fe2+, Fe3+, Mn2+, Mn3+, Zn and XO4 may be AsO4, PO4, SO4,VO4. Bands are assigned to the stretching and bending modes of SO42- AsO43- and HOAsO3 units. Raman spectroscopy readily distinguishes between the two minerals arsentsumebite and tsumebite. Raman bands attributed to arsenate are not observed in the Raman spectrum of tsumebite. Phosphate bands found in the Raman spectrum of tsumebite are not found in the Raman spectrum of arsentsumebite. Raman spectroscopy readily distinguishes the two minerals tsumebite and arsentsumebite.

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Some minerals are formed which show poorly defined X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of the oxyanions in such minerals. Among this group of minerals is mallestigite with formula Pb3Sb5+(SO4)(AsO4)(OH)6•3H2O. The objective of this research is to determine the molecular structure of the mineral mallestigite using vibrational spectroscopy. Raman and infrared bands are attributed to the AsO43- , SO42- and water stretching vibrations. Mallestigite is a mineral formed in ancient waste dumps such as occurs at Mallestiger, Carinthia, Austria and as such is a mineral of archaeological significance.

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The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.

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This paper describes modelling, estimation and control of the horizontal translational motion of an open-source and cost effective quadcopter — the MikroKopter. We determine the dynamics of its roll and pitch attitude controller, system latencies, and the units associated with the values exchanged with the vehicle over its serial port. Using this we create a horizontal-plane velocity estimator that uses data from the built-in inertial sensors and an onboard laser scanner, and implement translational control using a nested control loop architecture. We present experimental results for the model and estimator, as well as closed-loop positioning.

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In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

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The mineral schlossmacherite (H3O,Ca)Al3(AsO4,PO4,SO4)2(OH)6 , a multi-cation-multi-anion mineral of the beudantite mineral subgroup has been characterised by Raman spectroscopy. The mineral and related minerals functions as a heavy metal collector and is often amorphous or poorly crystalline, such that XRD identification is difficult. The Raman spectra are dominated by an intense band at 864 cm-1, assigned to the symmetric stretching mode of the AsO43- anion. Raman bands at 809 and 819 cm-1 are assigned to the antisymmetric stretching mode of AsO43- . The sulphate anion is characterised by bands at 1000 cm-1 (ν1), and at 1031, 1082 and 1139 cm-1 (ν3). Two sets of bands in the OH stretching region are observed: firstly between 2800 and 3000 cm-1 with bands observed at 2850, 2868, 2918 cm-1 and secondly between 3300 and 3600 with bands observed at 3363, 3382, 3410, 3449 and 3537 cm-1. These bands enabled the calculation of hydrogen bond distances and show a wide range of H-bond distances.

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The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

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Three-dimensional wagon train models have been developed for the crashworthiness analysis using multi-body dynamics approach. The contributions of the train size (number of wagon) to the frontal crash forces can be identified through the simulations. The effects of crash energy management (CEM) design and crash speed on train crashworthiness are examined. The CEM design can significantly improve the train crashworthiness and the consequential vehicle stability performance - reducing derailment risks.

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Kinematic models are commonly used to quantify foot and ankle kinematics, yet no marker sets or models have been proven reliable or accurate when wearing shoes. Further, the minimal detectable difference of a developed model is often not reported. We present a kinematic model that is reliable, accurate and sensitive to describe the kinematics of the foot–shoe complex and lower leg during walking gait. In order to achieve this, a new marker set was established, consisting of 25 markers applied on the shoe and skin surface, which informed a four segment kinematic model of the foot–shoe complex and lower leg. Three independent experiments were conducted to determine the reliability, accuracy and minimal detectable difference of the marker set and model. Inter-rater reliability of marker placement on the shoe was proven to be good to excellent (ICC = 0.75–0.98) indicating that markers could be applied reliably between raters. Intra-rater reliability was better for the experienced rater (ICC = 0.68–0.99) than the inexperienced rater (ICC = 0.38–0.97). The accuracy of marker placement along each axis was <6.7 mm for all markers studied. Minimal detectable difference (MDD90) thresholds were defined for each joint; tibiocalcaneal joint – MDD90 = 2.17–9.36°, tarsometatarsal joint – MDD90 = 1.03–9.29° and the metatarsophalangeal joint – MDD90 = 1.75–9.12°. These thresholds proposed are specific for the description of shod motion, and can be used in future research designed at comparing between different footwear.

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The observing failure and feedback instability might happen when the partial sensors of a satellite attitude control system (SACS) go wrong. A fault diagnosis and isolation (FDI) method based on a fault observer is introduced to detect and isolate the fault sensor at first. Based on the FDI result, the object system state-space equation is transformed and divided into a corresponsive triangular canonical form to decouple the normal subsystem from the fault subsystem. And then the KX fault-tolerant observers of the system in different modes are designed and embedded into online monitoring. The outputs of all KX fault-tolerant observers are selected by the control switch process. That can make sense that the SACS is part-observed and in stable when the partial sensors break down. Simulation results demonstrate the effectiveness and superiority of the proposed method.

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The paper investigates a detailed Active Shock Control Bump Design Optimisation on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 to reduce cruise drag at transonic flow conditions using Evolutionary Algorithms (EAs) coupled to a robust design approach. For the uncertainty design parameters, the positions of boundary layer transition (xtr) and the coefficient of lift (Cl) are considered (250 stochastic samples in total). In this paper, two robust design methods are considered; the first approach uses a standard robust design method, which evaluates one design model at 250 stochastic conditions for uncertainty. The second approach is the combination of a standard robust design method and the concept of hierarchical (multi-population) sampling (250, 50, 15) for uncertainty. Numerical results show that the evolutionary optimization method coupled to uncertainty design techniques produces useful and reliable Pareto optimal SCB shapes which have low sensitivity and high aerodynamic performance while having significant total drag reduction. In addition,it also shows the benefit of using hierarchical robust method for detailed uncertainty design optimization.

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A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle. Indeed, due to the vehicles' design and the actuation modes usually under consideration for underwater plateforms the number of actuator switchings must be kept to a small value to insure feasibility and precision. This is the main objective of the algorithm presented in this paper. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six-degrees-of freedom and one is minimally actuated with control motions in the vertical plane only.

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In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

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Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.