• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.66-72
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• 2004

PID control has been well used for several decades. For PID algorithms, some tuning methods are used for selecting PID parameters and with these selected parameters, PID control system is designed. But in some cases various kinds of performance indices are used instead of well-known tuning rules, and so variable type of performance index must be tested so that the designed control system meets the some specifications. For 2 DOF PID controller design this paper presents a linear combinational type of performance indices constituting of index for robust performance, which is obtained by h infinity norm of a weighted complementary sensitivity function, including other time domain indices such as error, energy and changing rate of control input. By numerical methods, the optimal 2 DOF PID parameters are obtained. Therefore various types of 2 degree of freedom PID controllers such as I-PD controller are used so that this two degree of freedom PID controllers may give more desirable output characteristics. Simulations are done with MATLAB m file and mdl files.

• Steel and Composite Structures
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• v.37 no.6
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• pp.663-678
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• 2020

This paper proposes a novel topology optimization method generating multiple materials for external linear plane crack structures based on the combination of IsoGeometric Analysis (IGA) and eXtended Finite Element Method (X-FEM). A so-called eXtended IsoGeometric Analysis (X-IGA) is derived for a mechanical description of a strong discontinuity state's continuous boundaries through the inherited special properties of X-FEM. In X-IGA, control points and patches play the same role with nodes and sub-domains in the finite element method. While being similar to X-FEM, enrichment functions are added to finite element approximation without any mesh generation. The geometry of structures based on basic functions of Non-Uniform Rational B-Splines (NURBS) provides accurate and reliable results. Moreover, the basis function to define the geometry becomes a systematic p-refinement to control the field approximation order without altering the geometry or its parameterization. The accuracy of analytical solutions of X-IGA for the crack problem, which is superior to a conventional X-FEM, guarantees the reliability of the optimal multi-material retrofitting against external cracks through using topology optimization. Topology optimization is applied to the minimal compliance design of two-dimensional plane linear cracked structures retrofitted by multiple distinct materials to prevent the propagation of the present crack pattern. The alternating active-phase algorithm with optimality criteria-based algorithms is employed to update design variables of element densities. Numerical results under different lengths, positions, and angles of given cracks verify the proposed method's efficiency and feasibility in using X-IGA compared to a conventional X-FEM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.85-92
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• 2018

Reductions of the electricity charge are achieved by demand management of the load. The demand management method of the load using ESS involves peak shifting, which shifts from a high demand time to low demand time. By shifting the load, the peak load can be lowered and the energy charge can be saved. Electricity charges consist of the energy charge and the basic charge per contracted capacity. The energy charge and peak load are minimized by Linear Programming (LP) and Quadratic Programming (QP), respectively. On the other hand, each optimization method has its advantages and disadvantages. First, the LP cannot separate the efficiency of the ESS. To solve these problems, the charge and discharge efficiency of the ESS was separated by Mixed Integer Linear Programming (MILP). Nevertheless, both methods have the disadvantages that they must assume the reduction ratio of peak load. Therefore, QP was used to solve this problem. The next step was to optimize the formula combination of QP and LP to minimize the electricity charge. On the other hand, these two methods have disadvantages in that the charge and discharge efficiency of the ESS cannot be separated. This paper proposes an optimization method according to the situation by analyzing quantitatively the advantages and disadvantages of each optimization method.

• Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.187-193
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• 2014

One of the hottest challenges in automotive industry is related to weight reduction in sheet metal forming processes, in order to produce a high quality metal part with minimal material cost. Stamping is the most widely used sheet metal forming process; but its implementation comes with several fabrication flaws such as springback and failure. A global and simple approach to circumvent these unwanted process drawbacks consists in optimizing the initial blank shape with innovative methods. The aim of this paper is to introduce an efficient methodology to deal with complex, computationally expensive multicriteria optimization problems. Our approach is based on the combination of methods to capture the Pareto Front, approximate criteria (to save computational costs) and global optimizers. To illustrate the efficiency, we consider the stamping of an industrial workpiece as test-case. Our approach is applied to the springback and failure criteria. To optimize these two criteria, a global optimization algorithm was chosen. It is the Simulated Annealing algorithm hybridized with the Simultaneous Perturbation Stochastic Approximation in order to gain in time and in precision. The multicriteria problems amounts to the capture of the Pareto Front associated to the two criteria. Normal Boundary Intersection and Normalized Normal Constraint Method are considered for generating a set of Pareto-optimal solutions with the characteristic of uniform distribution of front points. The computational results are compared to those obtained with the well-known Non-dominated Sorting Genetic Algorithm II. The results show that our proposed approach is efficient to deal with the multicriteria shape optimization of highly non-linear mechanical systems.

• Korean Journal of Community Nutrition
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• v.17 no.3
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• pp.329-340
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• 2012

Hypertension is a well-known risk factor for cardiovascular disease. Previous studies have shown that changes in diet and lifestyle factors can prevent the development of hypertension, but the combined effects of these modifiable factors on hypertension are not well established. The objective of this study is to investigate associations of diet and lifestyle factors, evaluated both individually and in combination, with prevalent hypertension among Korean adults. We analyzed data obtained from the 2007-2008 Korean National Health and Nutritional Examination Survey, a nationwide cross-sectional study using a stratified, multistage probability sampling design. The associations of 12 nutrient intakes and lifestyle factors with risk of hypertension were explored using restricted cubic spline regression and logistic regression models among 6,351 adults. Total energy and several nutrients and minerals, including, calcium, vitamin A, vitamin C, and sodium, showed non-linear relationships with the risk of prevalent hypertension. In multivariate logistic regression models, dietary score, obesity and alcohol intake were independently associated with the risk of prevalent hypertension, but smoking and physical activity were not. Overall, participants whose dietary habits and lifestyle factors were all in the low-risk group had 68% lower prevalence of hypertension (OR: 0.32, 95 CI: 0.14-0.74) compared to those who were at least one in the high-risk group of any dietary or lifestyle factors. The result suggests that combined optimal lifestyle habits are strongly associated with lower prevalence of hypertension among Korean adults.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.315-316
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• 2007

This paper presents a new methodology to improve movement database for a humanoid robot. The database is initially full of human motions so that the kinetics characteristics of human movement are immanent in it. then, the database is updated to the pseudo-optimal motions for the humanoid robot to perform more natural motions, which contain the kinetics characteristics of robot. for this, we use the evolutionary algorithm. the methodology consists of two processes : (1) the offline imitation learning of human movement and (2) the online generation of natural motion. The offline process improve the initial human motion database using the evolutionary algorithm and inverse dynamics-based optimization. The optimization procedure generate new motions using the movement primitive database, minimizing the joint torque. This learning process produces a new database that can endow the humanoid robot with natural motions, which requires minimal torques. In online process, using the linear combination of the motion primitive in this updated database, the humanoid robot can generate the natural motions in real time. The proposed framework gives a systematic methodology for a humanoid robot to learn natural motions from human motions considering dynamics of the robot. The experiment of catching a ball thrown by a man is performed to show the feasibility of the proposed framework.

• Journal of the korean society of oceanography
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• v.32 no.4
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• pp.163-170
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• 1997

Some CMP gathers acquired from shallow marine seismic reflection survey in offshore Korea do not show the hyperbolic trend of moveout. It originated from so-called swell effect of source and streamer, which are towed under rough sea surface during the data acquisition. The observed time deviations of NMO-corrected traces can be entirely ascribed to the swell effect. To correct these time deviations, a residual statics is introduced using Genetic Algorithms (GA) into the swell correction. A new class of global optimization methods known as GA has recently been developed in the field of Artificial Intelligence and has a resemblance with the genetic evolution of biological systems. The basic idea in using GA as an optimization method is to represent a population of possible solutions or models in a chromosome-type encoding and manipulate these encoded models through simulated reproduction, crossover and mutation. GA parameters used in this paper are as follows: population size Q=40, probability of multiple-point crossover P$_c$=0.6, linear relationship of mutation probability P$_m$ from 0.002 to 0.004, and gray code representation are adopted. The number of the model participating in tournament selection (nt) is 3, and the number of expected copies desired for the best population member in the scaling of fitness is 1.5. With above parameters, an optimization run was iterated for 101 generations. The combination of above parameters are found to be optimal for the convergence of the algorithm. The resulting reflection events in every NMO-corrected CMP gather show good alignment and enhanced quality stack section.

• Smart Structures and Systems
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• v.23 no.1
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• pp.1-14
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• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

• Korean Journal of Construction Engineering and Management
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• v.15 no.6
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• pp.26-34
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• 2014

Highway construction is a combination of linear, repetitive, and highly equipment intensive operations. Various types of construction equipment are deployed to ensure undisrupted performance of construction, and thus productivity improvement and cost-saving can be achieved through well-thought-out planning. The selection of construction equipment is dependent upon construction sequence, site conditions, and construction methods. In the process of planning, management should consider various types of construction methods per each type of construction operation. Also, management should map out proper construction equipment operation plan that takes the construction duration and cost measures into consideration. However, limited availability of historic data from the similar types of operations has been a stumbling block to proper construction planning, making the operations performed based upon experience and intuition guided by rules-of-thumb. As a consequence, the planing phase rarely provided an adequate validity in the implementation phase. The researchers developed a process logic for each construction type that management can utilize from early phase of highway construction planning process. Moreover, derived the construction equipment combination optimized for efficiency by using the process simulation technique. The developed method is expected to be useful for the decision-making process that aims to evaluate efficiency of various process plans and to ensure optimal selection of construction equipment for highway construction projects.

• Membrane Journal
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• v.28 no.2
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• pp.83-89
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• 2018

Hydrophobic porous PVDF hollow fiber membranes for Membrane Distillation (MD) were fabricated by a combination of thermally induced phase separation (TIPS) and stretching. The purpose of this study is to investigate the shape and operating conditions of the module and the effect of piping size on parallel connection. In the optimization experiment of the vacuum membrane distillation module, the flux decreased as the packing density and length of the membrane in the module increased. When the module was connected vertically, it was confirmed that the nearest to the inlet of the vacuum port was the highest flux. In selecting the size of the header pipe of the module, it was confirmed that the maximum flux is shown when the inner diameter area of the hollow fiber membrane and the inner diameter area of the header pipe are the same. Also, it is necessary to find the optimal linear velocity because the higher the linear velocity in the module, the higher the flux, but the pressure acting on the module also increases proportionally.