• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.629-634
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• 2000

Generally, the accuracy of motion control systems is strongly influenced by both the mechanical characteristics and servo characteristics of feed drive systems. In the fed drive systems of machine tools that consist of mechanical parts and electrical parts, a torsional vibration is often generated because of its elastic elements in torque transmission. Especially, a torsional vibration caused by the elasticity of mechanical elements might deteriorate the quick movement of system and lead to shorten the life time of the mechanical transmission elements. So it is necessary to analyze the electromechanical system mathematically to optimize the dynamic characteristics of the feed drive system. In this paper, based on the simplifies feed drive system model, radius errors due to position gain mismatch and servo response characteristic have been developed and an optimal criterion for tuning the gain of speed controller is discussed. The proportional and integral parameter gain of the feed drive controller are optimal design variables for the gain tuning of PI speed controller. Through the optimization problem formulation, both proportional and integral parameter are optimally tuned so as to compensate the radius errors by using the genetic algorithm. As a result, higher performance on circular profile tests has been achieved than the one with standard parameters.

• Membrane and Water Treatment
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• v.9 no.3
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• pp.155-162
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• 2018

Process modeling with activated sludge models (ASMs) is useful for the design and operational improvement of biological nutrient removal (BNR) processes. Effective utilization of ASMs requires the influent fraction analysis (IFA) of the wastewater treatment plant (WWTP). However, this is difficult due to the time and cost involved in the design and operation steps, thereby declining the simulation reliability. Harmony Search (HS) algorithm was utilized herein to determine the relationships between composite variables and state variables of the model IWA ASM1. Influent fraction analysis was used in estimating fractions of the state variables of the WWTP influent and its application to 9 wastewater treatment processes in South Korea. The results of influent $S_s$ and $Xs+X_{BH}$, which are the most sensitive variables for design of activated sludge process, are estimated within the error ranges of 8.9-14.2% and 3.8-6.4%, respectively. Utilizing the chemical oxygen demand (COD) fraction analysis for influent wastewater, it was possible to predict the concentrations of treated organic matter and nitrogen in 9 full scale BNR processes with high accuracy. In addition, the results of daily influent fraction analysis (D-IFA) method were superior to those of the constant influent fraction analysis (C-IFA) method.

• The KSFM Journal of Fluid Machinery
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• v.17 no.2
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• pp.48-53
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• 2014

A low-noise regenerative blower is developed for fuel cell application by combining the FANDAS-Regen code and design optimization algorithm under several performance constraints for flow capacity, static pressure, efficiency and power consumption. The optimized blower design model is manufactured with some impeller modification based on low noise design concept and tested by using aerodynamic performance chamber facility and narrow-band noise measurement apparatus. The measured results of the optimized blower satisfy the performance requirements and are also compared favorably with the FANDAS-Regen prediction results within a few percent relative error. Furthermore, the present study shows the remarkable noise reduction by 26 dBA can be achieved through design optimization and low noise design concept.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.119-126
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• 2002

In this paper, we present a new approach based on an elitist genetic algorithm for the task of aligning the position of a robot gripper using CCD cameras. The vision-based control scheme for the task of aligning the gripper with the desired position is implemented by image information. The relationship between the camera space location and the robot joint coordinates is estimated using a camera-space parameter modal that generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation. To find the joint angles of a robot manipulator for reaching the target position in the image space, we apply an elitist genetic algorithm instead of a nonlinear least square error method. Since GA employs parallel search, it has good performance in solving optimization problems. In order to improve convergence speed, the real coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using an elitist genetic algorithm with a real coding method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.1101-1107
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• 2004

This paper presents an optimization algorithm and technique for designing parallel Cyclic Redundancy Check (CRC) circuit, which is most widely adopted for error detection A new heuristic algorithm is developed to find as many shared terms as possible, thus eventually to minimize the number and level of the exclusive-or logic blocks in parallel CRC circuits. 16-bit and 32-bit CRC generators are designed with different types of Programmable Logic Devices, and it has been found that our new algorithm and architecture significantly reduce the delay.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.580-593
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• 2003

A joint design scheme has been proposed to optimize the source encoder and the modulation signal constellation based on the minimization of the end-to-end distortion including both the quantization error and channel distortion. The proposed scheme first optimizes the VQ codebook for a fixed modulation signal set, and then the modulation signals for the fixed VQ codebook. These two steps are iteratively repeated until they reach a local optimum solution. It has been shown that the performance of the proposed system can be enhanced by employing a new efficient mapping scheme between codevectors and modulation signals. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional system based on a conventional QAM modulation signal set and the VQ codebook designed for a noiseless channel.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.337-347
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• 2009

Generally, finite element models used in structural analysis have some uncertainties of the geometric dimensions, applied loads and boundary conditions, as well as in material properties due to the manufacturability of aluminum intensive body. Therefore, it is very important to refine or update a finite element model by correlating it with dynamic and static tests. The structural optimization problems of automotive body are considered for mechanical structures with initial stiffness due to preloading and in operation condition or manufacturing. As the mean compliance and deflection under preloading are chosen as the objective function and constraints, their sensitivities must be derived. The optimization problem is iteratively solved by a sequential convex approximation method in the commercial software. The design variables are corrected by the strain energy scale factor in the element levels. This paper presents an updated method based on the sensitivities of structural responses and the residual error vectors between experimental and simulation models.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.3
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• pp.40-46
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• 2008

This paper presents the optimal motion control for 3-axis SCARA robot by using $LabVIEW^{(R)}$. Specifically, for optimal motion control of 3-axis SCARA robot, we study velocity profile based on finite jerk(the first derivative of acceleration) and optimal gain tunig based on frequency response method by using $LabVIEW^{(R)}$. The velocity optimization with finite jerk aims at generating the smooth velocity profile of robot. Velocity profile based on finite jerk is acquired and applied to 3-axis SCARA robot by using $LabVIEW^{(R)}$. DSA(Dynamic Signal Analyzer) for frequency response method is programed by using $LabVIEW^{(R)}$. We obtain the bode plot of transfer function about 3-axis SCARA robot by using DSA, and perform the gain tuning considering dynamic characteristic based on the bode plot. These experiments have shown that the proposed motion control can reduce vibration displacement and response error rate each 33.7% and 51.7% of 3-axis SCARA robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4604-4622
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• 2015

It is not easy to reconstruct the geometrical characteristics of the distorted images captured by the devices. One of the most popular optimization methods is fast iterative shrinkage/ thresholding algorithm. In this paper, to deal with its approximation error and the turbulence of the decrease process, an adaptive proximal conjugate gradient (APCG) framework is proposed. It contains three stages. At first stage, a series of adaptive penalty matrices are generated iterate-to-iterate. Second, to trade off the reconstruction accuracy and the computational complexity of the resulting sub-problem, a practical solution is presented, which is characterized by solving the variable ellipsoidal-norm based sub-problem through exploiting the structure of the problem. Third, a correction step is introduced to improve the estimated accuracy. The numerical experiments of the proposed algorithm, in comparison to the favorable state-of-the-art methods, demonstrate the advantages of the proposed method and its potential.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3076-3092
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• 2020

An IKPCA-ELM-based intrusion detection method is developed to address the problem of the low accuracy and slow speed of intrusion detection caused by redundancies and high dimensions of data in the network. First, in order to reduce the effects of uneven sample distribution and sample attribute differences on the extraction of KPCA features, the sample attribute mean and mean square error are introduced into the Gaussian radial basis function and polynomial kernel function respectively, and the two improved kernel functions are combined to construct a hybrid kernel function. Second, an improved particle swarm optimization (IPSO) algorithm is proposed to determine the optimal hybrid kernel function for improved kernel principal component analysis (IKPCA). Finally, IKPCA is conducted to complete feature extraction, and an extreme learning machine (ELM) is applied to classify common attack type detection. The experimental results demonstrate the effectiveness of the constructed hybrid kernel function. Compared with other intrusion detection methods, IKPCA-ELM not only ensures high accuracy rates, but also reduces the detection time and false alarm rate, especially reducing the false alarm rate of small sample attacks.