Vehicle platoons are usually modelled as continuous dynamic systems. But the parameters of the embedded controllers require particular adaptation depending on the quality and changes commonly occurring in communicatio...
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Vehicle platoons are usually modelled as continuous dynamic systems. But the parameters of the embedded controllers require particular adaptation depending on the quality and changes commonly occurring in communication networks. These changes may lead to delays or in extreme cases to loss of information. Hence, these changes trigger the jump from one continuous state to another and may be considered as discrete events arising, in general, spontaneously. In this work, we use the formalism of hybrid automata to carry out a safety analysis of controlled vehicle platoons. We are interested in the safety verification of a platoon of vehicles, which communicate with each other via a wireless network. Our aim is to check, if a collision could take place within the platoon under a predefined control law including mode switches. In this paper, we report on results for the non-switching case and for pre-defined switching times. In addition, using different verification tools for this case study allows for the assessment of the performance of these tools and their limitations.
The grid links all resources in different structures widespread geographically into one logical system via internet, characterized with complexity of network structure, dynamism of network resources and autonomy of ea...
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The grid links all resources in different structures widespread geographically into one logical system via internet, characterized with complexity of network structure, dynamism of network resources and autonomy of each LAN. The high-efficient management of grid resources and high-efficient scheduling of tasks are the important contents in today's net grid research. Slices technology is the present quite popular popular technology, the application domain is widespread. The grid technology and the slice technology fuse in together, may create the more reasonable task scheduling and the scheduling of resources. In this article we divide the tasks into some small tasks assigned with scheduling priorities for each level, and then slice all resources in network into some time slices assigned with resource priorities according to trust mechanism. It promotes the effectiveness and high-efficiency by arranging task scheduling and resource scheduling in priority.
In this paper, the Prior Density Splitting Mixture Estimator (PDSME), a new Gaussian mixture filtering algorithm for nonlinear dynamical systems and nonlinear measurement equations, is introduced. This filter reduces ...
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In this paper, the Prior Density Splitting Mixture Estimator (PDSME), a new Gaussian mixture filtering algorithm for nonlinear dynamical systems and nonlinear measurement equations, is introduced. This filter reduces the linearization error which typically arises if nonlinear state and measurement equations are linearized to apply linear filtering techniques. For that purpose, the PDSME splits the prior probability density into several components of a Gaussian mixture with smaller covariances. The PDSME is applicable to both prediction and filter steps. A measure for the linearization error similar to the Kullback-Leibler distance is introduced allowing the user to specify the desired estimation quality. An upper bound for the computational effort can be given by limiting the maximum number of Gaussian mixture components.
This paper describes and demonstrates a mathematical algorithm that can monitor the physical parameters of the motor solely by observing the stator electrical currents. This method uses measurements of transient stato...
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ISBN:
(纸本)9781424428922
This paper describes and demonstrates a mathematical algorithm that can monitor the physical parameters of the motor solely by observing the stator electrical currents. This method uses measurements of transient stator currents to identify the parameters of an electromechanical model of the induction motor. These parameters are obtained from a relatively poor initial guess, which is constrained only to be within an order of magnitude of the physical parameters, by using a two-step strategy based upon nonlinear least-squares regression techniques. This makes the approach in this paper useful for diagnostic monitoring and energy scorekeeping. Experimental results are presented which demonstrate the effectiveness of this method on identifying the parameters of a 1 HP induction motor connected to a squirrel cage fan in an air-handling unit.
Shape optimization of shell roofs subjected to strong wind is camed out to mimmize the maximum vertical displacement. The three dimensional (3D) fluid flow analysis is performed to obtain highly precise dynamic wind l...
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Shape optimization of shell roofs subjected to strong wind is camed out to mimmize the maximum vertical displacement. The three dimensional (3D) fluid flow analysis is performed to obtain highly precise dynamic wind load. To reduce the large computational cost of the 3D analysis, the multignd method is employed to solve the pressure Poisson equation. The objective function of the optimization problem is expected to have strong nonlineanty. Employing Response Surface Model (RSM), the objective function is approximated as a smooth function so that computational cost of the optimization is reduced. Analyses for several experimental points are required to generate RSM. It is not practical to perform 3D analyses for all experimental points due to huge computational cost. Vanable Complexity Model (VCM) is useful for generating RSM. VCM is the method combining a high-fidelity model and a low-fidelity model. As the method of generating RSM, two kinds of methods are employed;(1) VCM (2) 3D analyses for all the experimental points. Optimized shapes are obtained by both methods. Although the value of the objective function of (1) is slightly larger than that of (2), the computation for (1) is much faster than that for (2).
This paper proposes a modified particle swarm optimization algorithm for engineering optimization problems with constraints, in which the penalty function is employed to the traditional PSO algorithm, and at the same ...
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This paper proposes a modified particle swarm optimization algorithm for engineering optimization problems with constraints, in which the penalty function is employed to the traditional PSO algorithm, and at the same time adjusts the personal optimum and global optimum to make PSO being able to solve the non-linear programming problems, then the multi-objective problem can be converted into single objective problem. Moreover, the constraint term played its role in the process of generating particles, those pariticles which don't meet the constraint condition are eliminated. The actual engineering design optimization problem is tested and the results show that the multi-objective particle swarm optimization algorithm can be used to solve the multi-objective constrained optimization problem. Comparison with Genetic Algorithm confirms that the proposed algorithm can find better solutions, and converge quickly.
In 1995, Mark Weiser introduced a scenario about the future life, where everyday objects are equipped with smart functions and the environment helps us to fulfill our everyday tasks. This paper shows how Weiser's ...
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In 1995, Mark Weiser introduced a scenario about the future life, where everyday objects are equipped with smart functions and the environment helps us to fulfill our everyday tasks. This paper shows how Weiser's scenario can be realized by today's available technologies. We combine PerFlows (to model the flow of daily tasks) and the Nexus context provisioning platform (to model and provide necessary context information to applications and devices). Furthermore, we present SmartGPS, which is able to provide fused location information even if the device is disconnected.
A bidirectional transformation consists of a pair of unidirectional transformations: a forward transformation that maps one data structure called source to another called view, and a backward transformation that refle...
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A bidirectional transformation consists of a pair of unidirectional transformations: a forward transformation that maps one data structure called source to another called view, and a backward transformation that reflects changes in the view to the source. Bidirectional transformation has many useful applications such as replicated data synchronization, presentation-oriented editor development, and software artifact synchronization. In a previous work, we proposed a framework in which a backward transformation is automatically generated from a forward transformation by derivation of a complementary function if the forward transformation is given by a program in a simple functional language. However, the language has a severe restriction that no variable is allowed to be used more than once. In this paper, we show that tupling transformation relaxes this restriction, allowing us to handle a wider class of bidirectional transformations that may contain duplications.
Operator training without a process model is necessary in certain plant manufacturing industry's applications because the process models from the control theory perspective are still not available. This paper desc...
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Operator training without a process model is necessary in certain plant manufacturing industry's applications because the process models from the control theory perspective are still not available. This paper describes an experiment that analyzed the benefits of 3D data visualization integrated in HMI for process control in combination with different types of operator training to obtain process knowledge. The benefits of interactive 3D slider training in identifying errors during operation could be proven.
Currently the demand of security is getting higher due to easy reproduction of digitally created multimedia data. Digital watermarking aims to embed secret information into content for copyright protection and authent...
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