This research investigates strategies to enable a deputy satellite to hover within a defined volume fixed in the vicinity of a chief satellite in a circular orbit for an extended period of time. Previous research deve...
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This research investigates strategies to enable a deputy satellite to hover within a defined volume fixed in the vicinity of a chief satellite in a circular orbit for an extended period of time. Previous research developed initial methodologies for maintaining restricted teardrop hover orbits that exist in a plane fixed within the chief's local reference frame. These methods use the natural drift of the deputy satellite in the relative frame and impulsive thrust to keep the deputy in a bounded volume relative to the chief, but do not address fuel optimality. This research extends and enhances that work by finding the optimal trajectories produced with discrete thrusts that minimize fuel spent per unit time and stay within the user-defined volume, thus providing a practical hover capability in the vicinity of the chief. The work assumes that the Clohessy-Wiltshire closeness assumption between the deputy and chief is valid. Using the new methodology developed in this work, feasible closed- and nonclosed-relative orbits are found and evaluated based on a fuel criterion and are compared with an easily calculated continuous-thrust baseline. It is shown that in certain scenarios (generally corresponding to a smaller total time of flight) a discrete-thrust solution provides a lower overall fuel cost than a continuous-thrust solution. A simple check is proposed that enables the mission planner to make the correct strategy choice.
In a three-dimensional (3-D) model-based objects tracking and recognition system, the key problem of objects location is to establish the relationship between 2-D objects image and 3-D model. Based on 3-D model projec...
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ISBN:
(纸本)9781424427239
In a three-dimensional (3-D) model-based objects tracking and recognition system, the key problem of objects location is to establish the relationship between 2-D objects image and 3-D model. Based on 3-D model projection and 2-D image feature extraction, a modified Hausdorff distance is used to establish the matching function. The relationship between matching parameters are described with a probability model, and the distribution of parameter evolves towards the direction of dominant character through probability model learning and the corresponding operation, which is proposed to solve the problem of overmany iteration and slow constringency velocity The experiments show that the optimal matching parameters between 3-D model and 2-D image feature can be found accurately and efficiently, and then the accurate object location is completed.
Genetic algorithm(GA) has a good robust and global optimization *** this paper,a supercavitation regime problem is transformed into an equivalent shape optimization problem by defining the objective function as a squa...
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Genetic algorithm(GA) has a good robust and global optimization *** this paper,a supercavitation regime problem is transformed into an equivalent shape optimization problem by defining the objective function as a square error integral of pressure *** combining the commercial CFD soft ANSYS with GA,this problem has been solved *** show that genetic algorithm is feasible and effective used in supercavitation flow analysis,the method is good for the reduction of computational complexity and more *** the frame can be expanded to study the cavitator optimization in which the regime optimization can be as a sub-optimization.
In this paper, a new method is presented for double nonlinear analysis of the simply-supported beam with elastic-perfectly plastic model. The major character of the new method is that the equilibrium state with elasti...
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In this paper, a new method is presented for double nonlinear analysis of the simply-supported beam with elastic-perfectly plastic model. The major character of the new method is that the equilibrium state with elastic-plastic large deformation is chosen as the study object. The constitutive law adopts elastic-perfectly plastic model and the shearing deformation is taken into account. The endpoint coordinates are given by means of coordinate recursion formulae, and the objective function is defined by unknown endpoint coordinates of slight segments. The optimization problem is established for double nonlinear analysis of the simply-supported beam, and the optimization program is programmed. Typical numerical examples are calculated by optimization algorithm, and the results are in very good agreement with those by FEM. So this paper provides a new and effective idea for double nonlinear problem of the simply-supported beam.
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic ...
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ISBN:
(纸本)078039335X
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task. In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic n...
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ISBN:
(纸本)0769524052
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations or the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.
A new approach for the optimization of essentially three-dimensional aerodynamic shapes for minimum drag is proposed. The method allows the handling of the nonlinear surfaces that are typical of complex aircraft junct...
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A new approach for the optimization of essentially three-dimensional aerodynamic shapes for minimum drag is proposed. The method allows the handling of the nonlinear surfaces that are typical of complex aircraft junctions such as a wing-body fairing. The optimization framework OPTIMAS, previously proposed and developed by the authors for the solution of the drag-minimization problem for two-dimensional airfoils, three-dimensional isolated wings, and three-dimensional wings in the presence of a body in succession, is extended in this paper to a significantly higher level of geometrical complexity of optimized aerodynamic configurations. The method is driven by accurate full Navier-Stokes evaluations of the objective function, and the optimization engine is based on genetic algorithms. The important features of the method are the ability to accurately handle multiple geometrical/aerodynamic constraints and a high level of computational efficiency, achieved through massive multilevel parallelization and a reduced-order-model approach. The method was applied to the optimization of a wing-body fairing for a generic business jet configuration at realistic transonic cruise flight conditions. The results demonstrate that the proposed approach achieves significant drag reduction in on- and offdesign conditions and can be used in an engineering environment.
In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. ...
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In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. The CLS method is formulated under a general framework for optimizing any discriminative objective functions including maximum mutual information (MMI), minimum classification error (MCE), minimum phone error (MPE)/minimum word error (MWE), etc. In this method, discriminative training of HMM is first cast as a constrained optimization problem, where Kullback-Leibler divergence (KLD) between models is explicitly imposed as a constraint during optimization. Based upon the idea of line search, we show that a simple formula of HMM parameters can be found by constraining the KLD between HMM of two successive iterations in an quadratic form. The proposed CLS method can be applied to optimize all model parameters in Gaussian mixture CDHMMs, including means, covariances, and mixture weights. We have investigated the proposed CLS approach on several benchmark speech recognition databases, including TIDIGITS, Resource Management (RM), and Switchboard. Experimental results show that the new CLS optimization method consistently outperforms the conventional EBW method in both recognition performance and convergence behavior.
One of major problems in image auto-annotation is the difference between the expected word counts vector and the resulted word counts vector. This paper presents a new approach to automatic image annotation-an algorit...
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One of major problems in image auto-annotation is the difference between the expected word counts vector and the resulted word counts vector. This paper presents a new approach to automatic image annotation-an algorithm called resulted word counts optimizer which is an extension to existing methods. An ideal annotator is defined in terms of recall quality measure. On the basis of the ideal annotator an optimization criterion is defined. it allows to reduce the difference between resulted and expected word counts vectors. The proposed algorithm can be used with various image auto-annotation algorithms because its generic nature. Additionally, it does not increase the computational complexity of the original annotation method processing phase. It changes output word probabilities according to a pre-calculated vector of correction coefficients. (C) 2008 Elsevier Ltd. All rights reserved.
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