This paper presents a state of the art of actual achievements in time-domain system identification using fractional models. It starts with some general aspects on time and frequency-domain representations, time-domain...
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ISBN:
(纸本)9780791848067
This paper presents a state of the art of actual achievements in time-domain system identification using fractional models. It starts with some general aspects on time and frequency-domain representations, time-domain simulation, and stability of fractional models. Then, an overview on system identification methods using fractional models is presented. Both equation-error and output-error-based models are detailed. In the former models, prior knowledge is generally used to fix differentiation orders;model coefficients are estimated using least squares. The latter models allow simultaneous estimation of model's coefficients and differentiation orders, using non linear programming. A real thermal example is identified using a fractional model and compared to a rational one.
The class of stochastic nonlinear programming (SNIP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications including those in the field of process systems engin...
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The class of stochastic nonlinear programming (SNIP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications including those in the field of process systems engineering. But despite the apparent importance of such problems, solution algorithms for these problems have found few applications due to severe computational and structural restrictions. To that effect, this work proposes a new algorithm for computationally efficient solution of the SNLP problems. Starting with the basic structure of traditional L-shaped method, the new algorithm called L-shaped BONUS incorporates reweighting scheme to ease computational load in the second stage recourse function calculation. The reweighting idea has been previously used successfully in optimization in BONUS, also an algorithm to solve SNLP problems. The proposed algorithm is analyzed using different case study problems including a blending problem relevant to process industry and a large scale novel sensor placement problem for water security networks. All problem results show considerable savings in computational time without compromising accuracy, the performance being better for Hammersley sequence sampling technique as compared to Monte Carlo sampling technique.
In this paper the problem of finding the maximum diameter of q equal non-overlapping circles on the surface of a sphere is considered. The packing problem resolution method proposed adopts a smoothing strategy using a...
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The multi-threshold-voltage CMOs (MTCMOS) technique is very effective for reducing leakage power. Previously, sleep transistors were connected the virtual ground lines to reduce the power consumption, and a Distribute...
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ISBN:
(纸本)9781424421664
The multi-threshold-voltage CMOs (MTCMOS) technique is very effective for reducing leakage power. Previously, sleep transistors were connected the virtual ground lines to reduce the power consumption, and a Distributed Sleep Transistor Network (DSTN) was proposed to reduce the instantaneous current. This paper presents a research on how to find the near optimal solution for the sleep transistor sizing problem in the DSTN structure. This paper adopts Lagrange Successive Over-Relaxation (SOR) iterative method which is frequently used in the optimization field. The method makes sure the Lagrange Multiplier satisfying the extreme conditions during the adjustment in each iteration, in order to find the near-optimum of the problem. Our experimental results are very exciting compared with the nonlinear programming.
This paper addresses the congestion management problem avoiding offline transmission capacity limits related to stability. These limits on line power flows are replaced by optimal power flow-related constraints that e...
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ISBN:
(纸本)9781424419050
This paper addresses the congestion management problem avoiding offline transmission capacity limits related to stability. These limits on line power flows are replaced by optimal power flow-related constraints that ensure an appropriate level of security, mainly targeting voltage instabilities, which are the most common source of stability problems. Results from an illustrative case study based on the IEEE 24-bus Reliability Test System are analyzed. Conclusions are duly drawn.
The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases a...
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The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration - the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.
The nonpreemptive priority queues are effective for performance evaluations of production/manufacturing systems, inventory control and computer and telecommunication systems. Due to uncontrollable factors, parameters ...
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In this paper, we focus on block-angular nonlinear integer programming problems which is often seen as a mathematical model of large-scale discrete systems optimization. In order to make use of the special structure o...
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The purpose of this paper is to present a new method for automatic 3-C 3-D VSP wavefield separation. The method uses an iterative global non-linear optimization scheme, which includes two major steps: automatic 3-C ve...
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ISBN:
(纸本)9781605604749
The purpose of this paper is to present a new method for automatic 3-C 3-D VSP wavefield separation. The method uses an iterative global non-linear optimization scheme, which includes two major steps: automatic 3-C velocity analysis and wave-by-wave extraction/ subtraction. Regular waves (P down and up, P-S down and up, etc.) are extracted from the 3-C wavefield one wave at a time. Automatic velocity analysis predicts the strongest wave, which is extracted and subtracted. The next strongest wave now becomes the dominant wave and the process is repeated. As each new event is extracted, all previous removed events are re-examined and *** 2008, European Association of Geoscientists and Engineers.
For estimation and fusion tasks it is inevitable to approximate a Gaussian mixture by one with fewer components to keep the complexity bounded. Appropriate approximations can be typically generated by exploiting the r...
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ISBN:
(纸本)9783000248832
For estimation and fusion tasks it is inevitable to approximate a Gaussian mixture by one with fewer components to keep the complexity bounded. Appropriate approximations can be typically generated by exploiting the redundancy in the shape description of the original mixture. In contrast to the common approach of successively merging pairs of components to maintain a desired complexity, the novel Gaussian mixture reduction algorithm introduced in this paper avoids to directly reduce the original Gaussian mixture. Instead, an approximate mixture is generated from scratch by employing homotopy continuation. This allows starting the approximation with a single Gaussian, which is constantly adapted to the progressively incorporated true Gaussian mixture. Whenever a user-defined bound on the deviation of the approximation cannot be maintained during the continuation, further components are added to the approximation. This facilitates significantly reducing the number of components even for complex Gaussian mixtures.
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