10 resultados para First order theories

em Deakin Research Online - Australia


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In this paper, we suggest the idea of separately treating the connectivity and communication model of a Wireless Sensor Network (WSN). We then propose a novel connectivity model for a WSN using first order Reed-Muller Codes. While the model has a hierarchical structure, we have shown that it works equally well for a Distributed WSN. Though one can use any communication model, we prefer to use the communication model suggested by Ruj and Roy [1] for all computations and results in our work. Two suitable secure (symmetric) cryptosystems can then be applied for the two different models, connectivity and communication respectively. By doing so we have shown how resiliency and scalability are appreciably improved as compared to Ruj and Roy [1].

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This paper reports a new result on the fault detection of dynamical systems by employing only first-order functional observers. Indeed, we show that fault detection can be achieved by utilizing first-order functional observers. The advantages for having such simple structured observers are obvious from the economical and practical points of view as significant cost saving can be achieved. We derive existence conditions and an algorithm for the generation of residual signals to detect faults using firstorder functional observers. Two numerical examples are given to illustrate the proposed fault detection scheme. In one of the examples, a two-area interconnected power system with reheat thermal turbines is considered where only a first-order functional observer is designed to detect faults in the power system.

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This paper deals with blind separation of spatially correlated signals mixed by an instantaneous system. Taking advantage of the fact that the source signals are accessible in some man-made systems such as wireless communication systems, we preprocess the source signals in transmitters by a set of properly designed first-order precoders and then the coded signals are transmitted. At the receiving side, information about the precoders are utilized to perform signal separation. Compared with the existing precoder-based methods, the new method only employs the simplest first-order precoders, which reduces the delay in data transmission and is easier to implement in practical applications.

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Efficient and accurate finite elements are crucial for finite element analysis to provide adequate prediction of the structural behavior. A large amount of laminated plate elements have been developed for finite element analysis of laminated composite plates based on the various lamination theories. A recent and complete review of the laminated finite elements based on the higher-order shear deformation theories, including the global higher-order theories, zig-zag theories and the global-local higher-order theories is presented in this paper. Finally some points on the development of the laminated plate elements are summarized.

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This paper presents a brief study on the design and performance comparison of conventional first-order and super-twisting second-order sliding mode observers for some nonlinear control systems. Estimation accuracy, fast response, chattering effect, peaking phenomenon and robustness are considered for nonlinear ystems under observer-based output feedback control and state feedback control.

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A large amount of finite elements have been developed for finite element analysis of laminated composite plates. The laminated plate theories are reviewed and summarized in this paper. The focus of this review is on the recently developed laminated finite elements since 1990. The 2-D triangular and quadrilateral displacement-based and mixed/hybrid-based finite element models, which were developed based on the first-order shear deformation theories, the higher-order shear deformation theories, the zig-zag theories and the global-local higher-order deformation theories, and the layer-wise laminated plate theories are reviewed in this paper and also their related patents. Finally, some points on the development of the laminated finite elements are summarized.

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In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

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In this study, we are focusing on the investigation of the effects of gradient patterns on mechanical behavior of functionally-graded carbon nanotube-reinforced nanocomposites and considering typical beams made of such nanocomposites. Both analytic and finite element-based numerical models were developed. Analytic model was developed based on the first-order shear deformation and Timoshenko beam theories meanwhile finite element models were developed using Abaqus in conjunction with user-defined subroutines for defining the continuously gradient material properties for different gradient patterns. Position-dependent elastic modulus equations for four continuously graded patterns were studied. A nongraded pattern was used for benchmarking with the same geometry and total carbon nanotube (CNT) contents. For validation and verification, the results on both deflection and stress of these nanocomposite beams were analyzed, which clearly showed high influence from gradient patterns on these mechanical behaviors of such beams.

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Abstract Motivated by the previously documented discrepancy between actual and predicted power, the present paper provides new tools for analyzing the local asymptotic power of panel unit root tests. These tools are appropriate in general when considering panel data with a dominant autoregressive root of the form ρi=1+ciN-κT-τ, where i=1,...,N indexes the cross-sectional units, T is the number of time periods and ci is a random local-to-unity parameter. A limit theory for the sample moments of such panel data is developed and is shown to involve infinite-order series expansions in the moments of ci, in which existing theories can be seen as mere first-order approximations. The new theory is applied to study the asymptotic local power functions of some known test statistics for a unit root. These functions can be expressed in terms of the expansions in the moments of ci, and include existing local power functions as special cases. Monte Carlo evidence is provided to suggest that the new results go a long way toward bridging the gap between actual and predicted power.

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This paper examines the design of minimal-order residual generators for the purpose of detecting and isolating actuator and/or component faults in dynamical systems. We first derive existence conditions and design residual generators using only first-order observers to detect and identify the faults. When the first-order functional observers do not exist, then based on a parametric approach to the solution of a generalized Sylvester matrix equation, we develop systematic procedures for designing residual generators utilizing minimal-order functional observers. Our design approach gives lower-order residual generators than existing results in the literature. The advantages for having such lower-order residual generators are obvious from the economical and practical points of view as cost saving and simplicity in implementation can be achieved, particularly when dealing with high-order complex systems. Numerical examples are given to illustrate the proposed fault detection and isolation schemes. In all of the numerical examples, we design minimum-order residual generators to effectively detect and isolate actuator and/or component faults in the system.