11,729 research outputs found
Quantum-classical correspondence in localization of eigenstates for a system having mixed-type classical dynamics
No full text©1999 The American Physical Society
URL: http://link.aps.org/abstract/PRE/v59/p5384
DOI: 10.1103/PhysRevE.59.5384
PACS: 05.45.-aWe have examined the localization properties of quantum eigenstates for a system having mixed-type classical dynamics. Emphasis is given to the structure of eigenfunctions and the local spectral density of states. The nature of strongly localized eigenstates can be explained by considering the corresponding classical motion on the Kolmogorov-Arnold-Moser tori. The weak localization of nearly delocalized eigenstates is not a quantum effect as is dynamical localization but a consequence of classical dynamics. [S1063-651X(99)15605-8].S. W. Kim thanks, with pleasure, Professor E. J. Heller and the colleagues of his group, especially Dr. L. Kaplan, of Harvard University, for their hospitality during his visit when a part of this work was done. This research was supported by the Ministry of Science and Technology of Korea under the project ‘‘High Performance Computing-Computational Science and Engineering’’ (HPC-COSE), and by the Agency for Defense Development (ADD) of Korea
PID control design with exhaustive dynamic encoding algorithm for searches (eDEAS)
No full textThis paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang's and Ho's methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.X113sciescopuskc
Parameter identification of induction motors using dynamic encoding algorithm for searches (DEAS)
No full textIn this paper, a newly developed optimization algorithm, called the dynamic encoding algorithm for searches (DEAS), is introduced and applied to the parameter identification of an induction motor for vector control and fault detection. Digital simulations are conducted on startup with no load and normal operation with load perturbations. DEAS is compared with the continuous-time prediction error method and the genetic algorithm via identification performance using the startup signals. The capability of onload identification using the proposed technique is also verified with transient signals. Consequently, DEAS is shown to locate more precise parameter values than both the compared methods especially with much faster execution time than the genetical algorithm.X1132Nsciescopu
New encoding/converting methods of binary GA/real-coded GA
No full textThis paper presents new encoding methods for the binary genetic algorithm (BGA) and new converting methods for the real-coded genetic algorithm (RCGA). These methods are developed for the specific case in which some parameters have to be searched in wide ranges since their actual values are not known. The oversampling effect which occurs at large values in the wide range search are reduced by adjustment of resolutions in mantissa and exponent of real numbers mapped by BGA. Owing to an intrinsic similarity in chromosomal operations, the proposed encoding methods are also applied to RCGA with remapping (converting as named above) from real numbers generated in RCGA. A simple probabilistic analysis and benchmark with two ill-scaled test functions are carried out. System identification of a simple electrical circuit is also undertaken to testify effectiveness of the proposed methods to real world problems. All the optimization results show that the proposed encoding/converting methods are more suitable for problems with ill-scaled parameters or wide parameter ranges for searching.open112sciescopu
Design of incremental fuzzy PI controllers for a gas-tbrbine plant
No full textIn this paper, incremental fuzzy proportional integral (PI) speed and temperature controllers for a heavy-duty gas-turbine plant are presented. To improve performance, an analysis of incremental fuzzy PI control is provided, and new fuzzy control rules are proposed. In applying the fuzzy PI control to a gas-turbine plant, all gains are optimized by an adaptive genetic algorithm. We show the performance improvement of the proposed controller compared with conventional PI controller via simulations.X1130sciescopu
Numerical method for global optimisation: dynamic encoding algorithm for searches
No full textA fast and reliable non-gradient optimisation method is proposed. The basic structure of the proposed numerical method is a binary matrix in which each row represents an encoded string for the corresponding parameter. The operations of adding a binary digit and performing an increment or a decrement to a selected row make successive approximations of the local minima, and the restart is undertaken from an unexplored initial matrix as an escape scheme. To verify the feasibility of the proposed method for global optimisation, several test functions are optimised as a benchmark, and the parameter identification of an induction motor is carried out on experimental data. Both the results of the benchmarking and the parameter identification show that the proposed non-gradient optimisation method is capable of fast and reliable global search for various problems.X1113sciescopu
A fast computational optimization method: Univariate dynamic encoding algorithm for searches (uDEAS)
No full textThis paper proposes a new computational optimization method modified from the dynamic encoding algorithm for searches (DEAS). Despite the successful optimization performance of DEAS for both benchmark functions and parameter identification, the problem of exponential computation time becomes serious as problem dimension increases. The proposed optimization method named univariate DEAS (uDEAS) is especially implemented to reduce the computation time using a univariate local search scheme. To verify the algorithmic feasibility for global optimization, several test functions are optimized as benchmark. Despite the simpler structure and shorter code length, function optimization performance show that uDEAS is capable of fast and reliable global search for even high dimensional problems.open111013sciescopu
Improved Rayleigh wave velocity measurement for nondestructive early-age concrete monitoring
No full textA modified one-sided technique is proposed for Rayleigh wave ( R-wave) velocity measurement in concrete. Wave scattering from material heterogeneity and near-field effects may disrupt sensed R-wave signals in concrete, which is manifested as signal dispersion. Conventional one-sided measurement techniques for concrete do not consider dispersion of R-waves. In this study, the maximum energy arrival concept is adopted to determine the wave velocity by employing continuous wavelet transform. Experimental and numerical studies are performed to show the effectiveness of the proposed method. The method is applied to monitor the strength development of early-age concrete exposed to various curing conditions. Results reveal that the proposed method can be effectively used to measure the R-wave velocity in concrete structures and further to monitor the development of compressive strength in early-age concrete, regardless of the concrete moist curing condition.This work was supported by both a research project of the Ministry of
Construction and Transportation (Grant No. 05CORETECH-C19) and an
engineering research center (ERC), Smart Infrastructure Technology Research
Center (SISTeC), program of Korea Science and Engineering Foundation
(Grant No. R11-2002-101-03001-0). Thanks go to Jin-Keun Kim at KAIST
and Won-Joon Song at RIST for their valuable discussions on the results,
and Jeong-Su Kim and Ji-Young Min, both at KAIST, for their help preparing
the experiments.
Maximization of poly-beta-hydroxybutyrate accumulation by potassium limitation in Methylobacterium organophilum and its related metabolic analysis
No full textWhen methanol was the sole carbon source, Methylobacterium organophilum NCIB 11278, a facultative methylotroph, accumulated poly-beta-hydroxybutyrate (PHB) as 59% (w/w) of dry cell weight under potassium limitation, 37% under sulfate limitation, and 33% under nitrogen limitation. Based on a stoichiometric analysis of PHB synthesis from methanol, it was suspected that PHB synthesis is accompanied by the overproduction of energy, either 6-10 ATP and 1 FADH(2), or 6 ATP and 3 NADPH to balance the NADH requirement, per PHB monomer. This was confirmed by observation of increased intracellular ATP levels during PHB accumulation. The intracellular ATP with limited potassium, sulfate, and ammonium increased to 0.185, 0.452, and 0.390 mu moles ATP/g Xr (residual cell mass) during PHB accumulation, respectively. The intracellular ATP level under potassium limitation was similar to that when there was no nutrient Limitation and no PHB accumulation, 0.152-0.186 mu moles ATP/g Xr. We propose that the maximum PHB accumulation observed when potassium was limited is a result of the energy balance during PHB accumulation. Microorganisms have high energy requirements under potassium limitation. Enhanced PHB accumulation, in ammonium and sulfate limited conditions with the addition of 2,4-dinitrophenol, which dissipates surplus energy, proves this assumption. With the addition of 1 mM of 2,4-dinitrophenol, the PHB content increased from 32.4% to 58.5% of dry cell weight when nitrogen Limited and from 15.1% to 31.0% of dry cell weight when sulfate limited
Consistent normalized least mean square filtering with noisy data matrix
No full textWhen the ordinary least squares method is applied to the parameter estimation problem with noisy data matrix, it is well-known that the estimates turn out to be biased. While this bias term can be somewhat reduced by the use of models of higher order, or by requiring a high signal-to-noise ratio (SNR), it can never be completely removed. Consistent estimates can be obtained by means of the instrumental variable method (IVM),or the total/data least squares method (TLS/DLS). In the adaptive setting for the such problem, a variety of least-mean-squares (LMS)-type algorithms have been researched rather than their recursive versions of IVM or TLS/DLS that cost considerable computations. Motivated by these observations, we propose a consistent LMS-type algorithm for the data least square estimation problem. This novel approach is based on the geometry of the mean squared error (MSE) function, rendering the step-size normalization and the heuristic filtered estimation of the noise variance, respectively, for fast convergence and robustness to stochastic noise. Monte Carlo simulations of a zero-forcing adaptive finite-impulse-response (FIR) channel equalizer demonstrate the efficacy of our algorithm.X1127sciescopu
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