• Journal of Power Electronics
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• v.4 no.3
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• pp.127-137
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• 2004

This paper introduces a hybrid induction motor control using a genetically optimized pseudo-on-line method. Optimization results from the use of a look-up table based on genetic algorithms to find the global optimum of an unconstrained optimization problem. The approach to induction motor control includes a pseudo-on-line procedure that optimally estimates parameters of a fuzzy PID (FPID) controller. The proposed hybrid genetic fuzzy PID (GFPID) controller is applied to speed control of a 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed controller performs better than conventional FPID and PID controllers. The contribution of this paper is the introduction of a high performance hybrid form of induction motor control that makes on-line and real-time control of the drive system possible.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.215-235
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• 2017

Foraging is a biological process, where a bacterium moves to search for nutriments, and avoids harmful substances. This paper proposes a hybrid approach integrating the bacterial foraging optimization algorithm (BFOA) in a radial basis function neural network, applied to image classification, in order to improve the classification rate and the objective function value. At the beginning, the proposed approach is presented and described. Then its performance is studied with an accent on the variation of the number of bacteria in the population, the number of reproduction steps, the number of elimination-dispersal steps and the number of chemotactic steps of bacteria. By using various values of BFOA parameters, and after different tests, it is found that the proposed hybrid approach is very robust and efficient for several-image classification.

• Journal of Power System Engineering
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• v.17 no.6
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• pp.108-114
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• 2013

This paper describes process optimization for thermal-sprayed Co-based self-flux alloy coating by Taguchi method. Co-based self-flux alloy coatings were fabricated according to $L_9(3^4)$ orthogonal array using flame spray process. Hardness test and wear test were performed, the results were analyzed by analysis of variance(ANOVA) considering a multi response signal to noise ratio(MRSN). From the results of ANOVA, the optimal combination of the flame spray parameters on Co-based self-flux alloy coating could be predicted. The calculated hardness and wear rate of the coatings by ANOVA were found to be close to that of confirmation experimental result.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.52-63
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• 2017

The inventory level of concurrent spare parts (CSP) has a significant impact on the availability of a weapon system. A failure rate function might be of particular importance in deciding the CSP inventory level. We developed a CSP optimization model which provides a compromise between purchase costs and shortage costs on the basis of the Weibull and the exponential failure rate functions, assuming that a failure occurs according to the (non-) homogeneous Poisson process. Computational experiments using the data obtained from the Korean Navy identified that, throughout the initial provisioning period, the optimization model using the exponential failure rate tended to overestimate the optimal CSP level, leading to higher purchase costs than the one using the Weibull failure rate. A Pareto optimality was conducted to find an optimal combination of these two failure rate functions as input parameters to the model, and this provides a practical solution for logistics managers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1483-1492
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• 2001

A robust optimization procedure is applied to determine the design of the laminated composite plates with buckling constraints. In order to investigate the variation effect to the whole performance of a structure, both design variables and system parameters are assumed as random variables about their nominal values. The robust optimization method has advantages that the mean value and the variation of the performance function are controlled simultaneously and the second order sensitivity information is not required. Considering the information of uncertainty, robust optima for the buckling load of the laminated composite plates with cut-out is obtained. The robustness of the structures is compared to that of the deterministic optimization using scaling factors.

• Smart Structures and Systems
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• v.11 no.1
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• pp.69-86
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• 2013

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

• Steel and Composite Structures
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• v.29 no.1
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• pp.39-51
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• 2018

Position of a circular or elliptical cutout within an orthotropic plate has great influence on its buckling behavior. This paper aims at finding the optimal position (both location and orientation) of a single circular/elliptical cutout, within an orthotropic rectangular plate, that maximizes the critical buckling load. We consider linear buckling of simply supported orthotropic plates under uniaxial edge loads. To obtain the optimal positions of the cutouts, we have employed a MATLAB optimization routine coupled with buckling computation in ANSYS. Our results show that the position of the cutout that maximizes the buckling load has great dependence on the material properties, laminate configurations, and the geometrical parameters of the plate. These optimal results, for a number of plate geometries and cutout sizes, are reported in this paper. These results will be useful in the design of perforated orthotropic plates against buckling failure.

• Steel and Composite Structures
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• v.19 no.4
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• pp.995-1009
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• 2015

This study presents design optimization of spot welded structures to attain maximum strength by using the Nelder-Mead (Simplex) method. It is the main idea of the algorithm that the simulation run is executed several times to satisfy predefined convergence criteria and every run uses the starting points of the previous configurations. The material and size of the sheet plates are the pre-assigned parameters which do not change in the optimization cycle. Locations of the spot welds, on the other hand, are chosen to be design variables. In order to calculate the objective function, which is the maximum equivalent stress, ANSYS, general purpose finite element analysis software, is used. To obtain global optimum locations of spot welds a methodology is proposed by modifying the Nelder-Mead (Simplex) method. The procedure is applied to a number of representative problems to demonstrate the validity and effectiveness of the proposed method. It is shown that it is possible to obtain the global optimum values without stacking local minimum ones by using proposed methodology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.543-551
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• 2001

This paper is concerned with optimization of a motor torque to drive Parking Sign system. It needs to minimize powers for stand alone operation and requires the optimized parameters in order to move the plates in the minimum torque. The operation can be represented as a complicated non-linear equation which is difficult to solve by general optimization techniques. In this paper, the dynamic equations of the system are derived, also the suitable Genetic Algorithm is designed to solve the equations. Computer simulation shows the availability of this method.