• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.11a
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• pp.166-171
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design for the application-based exclusive rolling element bearings, this study propose design methodologies by using a genetic-based combinatorial optimization. By the presence of discrete variables such as the number of rolling element (standard component) and by the engineering point of views, the design problem of the rolling element bearing can be characterized by the combinatorial optimization problem as a fully discrete optimization. A genetic algorithm is used to efficiently find a set of the optimum discrete design values from the pre-defined variable sets. To effectively deal with the design constraints and the multi-objective problem, a ranking penalty method is suggested for constructing a fitness function in the genetic-based combinatorial optimization. To evaluate the proposed design method, a robust performance analyzer of ball bearing based on quasi-static analysis is developed and the computer program is applied to some design problems, 1) maximize fatigue life, 2) maximize stiffness, 3) maximize fatigue life and stiffness, of a angular contact ball bearing. Optimum design results are demonstrate the effectiveness of the design method suggested in this study. It believed that the proposed methodologies can be effectively applied to other multi-objective discrete optimization problems.

• Geomechanics and Engineering
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• v.10 no.6
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• pp.709-726
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• 2016

Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.47.2-47.2
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• 2010

For reducing outer reflection in mono-crystalline silicon solar cell, wet texturing process has been adapted for long period of time. Nowadays mixed solution with potassium hydroxide and isopropyl alcohol is used in silicon surface texturing by most manufacturers. In the process of silicon texturing, etch rate is very critical for effective texturing. Several parameters influence the result of texturing. Most of all, temperature, process time and concentration of potassium hydroxide can be classified as important factors. In this paper, temperature, process time and concentration of potassium hydroxide were set as major parameters and 3-level test matrix was created by using robust design for the optimized condition. The process optimization in terms of lowest reflection and stable etch rate can be traced by using robust design method.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.129-139
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• 2016

This paper presented a robust ship scheduling model using the quadratic programming problem. Given a set of available carriers under control and a set of cargoes to be transported from origin to destination, a robust ship scheduling that can minimize the mean-variance objective function with the required level of profit can be modeled. Computational experiments concerning relevant maritime transportation problems are performed on randomly generated configurations of tanker scheduling in bulk trade. In the first stage, the optimal transportation problem to achieve maximum revenue is solved through the traditional set-packing model that includes all feasible schedules for each carrier. In the second stage, the robust ship scheduling problem is formulated as mentioned in the quadratic programming. Single index model is used to efficiently calculate the variance-covariance matrix of objective function. Significant results are reported to validate that the proposed model can be utilized in the decision problem of ship scheduling after considering robustness and the required level of profit.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1132-1138
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• 2009

The spring constants of primary suspensions for a railway vehicle are optimized by a robust design process, in which the response surface models(RSMs) of their dynamic responses are constructed via the design of experiment(DOE). The robust design process requires an intensive computation to evaluate exactly a probabilistic feasibility for the robustness of dynamic responses with their probabilistic variances for the railway vehicle. In order to overcome the computational process, the process capability index $C_{pk}$ is introduced which enables not only to show the mean value and the scattering of the product quality to a certain extent, but also to normalize the objective functions irrespective of various different dimensions. This robust design, consequently, becomes to optimize the $C_{pk}$ subjected to constraints, i.e. 2, satisfying six sigma. The proposed method shows not only an improvement of some $C_{pk}$ violating the constraints obtained by the conventional optimization, but also a significant decrease of the variance of the $C_{pk}$.

• Journal of Power Electronics
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• v.12 no.4
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• pp.538-547
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• 2012

This paper presents two different robust controllers for boost converters with two stages in a cascade. The first robust controller is monovariable; that is, the duty-cycle is the same for the two switches. The monovariable controller ensures that some prescribed constraints on pole placement and control effort are met, and optimizes the load disturbance rejection, while takes into account the uncertainty in certain parameters. The first controller is then compared with a multivariable robust controller; that is, with independent duty cycles in each switch. The multivariable controller takes into account the same uncertainty, constraints and optimization function. The comparison shows that the multivariable controller performs better at the expense of a slightly more complex implementation; that is, the multivariable controller provides a better rejection of the load disturbance. The paper also describes simulations and experimental results that are in perfect agreement with theoretical derivations.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.487-492
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• 2007

This paper presents the development of digital robust fuzzy controller for uncertain nonlinear systems. The proposed approach is based on the intelligent digital redesign(IDR) method with considering the relaxed stability condition of fuzzy control system. The term IDR in the concerned system is to convert an existing analog robust control into an equivalent digital counterpart in the sense of the state-matching. We shows that the IDR problem can be reduced to find the digital fuzzy gains minimizing the norm distance between the closed-loop states of the analog and digital robust control systems. Its constructive conditions are expressed as the linear matrix inequalities(LMIs) and thereby easily tractable by the convex optimization techniques. Based on the nonquadratic Lyapunov function, the robust stabilization conditions are given for the sampled-data fuzzy system, and hence less conservative. A numerical example, chaotic Lorentz system, is demonstrated to visualize the feasibility of the proposed methodology.

• Structural Engineering and Mechanics
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• v.67 no.1
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• pp.33-43
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• 2018

The dynamic output-feedback robust control method based on linear matrix inequality (LMI) method is presented for suppressing vibration response of a functionally graded material (FGM) beam with piezoelectric actuator/sensor layers in this paper. Based on the reduced model obtained by using direct mode truncation, the linear fractional state space representation of a piezoelectric FGM beam with material properties varying through the thickness is developed by considering both the inherent uncertainties in constitution material properties as well as material distribution and the model error due to mode truncation. The dynamic output-feedback robust H-infinity control law is implemented to suppress the vibration response of the piezoelectric FGM beam and the LMI method is utilized to convert control problem into convex optimization problem for efficient computation. In numerical studies, the flexural vibration control of a cantilever piezoelectric FGM beam is considered to investigate the accuracy and efficiency of the proposed control method. Compared with the efficient linear quadratic regulator (LQR) widely employed in literatures, the proposed robust control method requires less control voltage applied to the piezoelectric actuator in the case of same control performance for the controlled closed-loop system.

• Journal of applied mathematics & informatics
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• v.30 no.5_6
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• pp.699-717
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• 2012

In this paper, we deal with the robust mixed $H_2/H_{\infty}$ guaranteed-cost control problem involving uncertain neutral stochastic distributed delay systems. More precisely, the aim of this problem is to design a robust mixed $H_2/H_{\infty}$ guaranteed-cost controller such that the close-loop system is stochastic mean-square exponentially stable, and an $H_2$ performance measure upper bound is guaranteed, for a prescribed $H_{\infty}$ attenuation level ${\gamma}$. Therefore, the fast convergence can be fulfilled and the proposed controller is more appealing in engineering practice. Based on the Lyapunov-Krasovskii functional theory, new delay-dependent sufficient criteria are proposed to guarantee the existence of a desired robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which are derived in terms of linear matrix inequalities(LMIs). Furthermore, the design problem of the optimal robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which minimized an $H_2$ performance measure upper bound, is transformed into a convex optimization problem with LMIs constraints. Finally, two simulation examples illustrate the design procedure and verify the expected control performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.45-54
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• 1998

For proper release of side airbags, the onset of crash should be detected first. After crash detection, the algorithm has to make a decision whether the side airbag deployment is necessary. If the deployment is necessary, proper timing has to be provided for the maximum protection of driver or passenger. The side airbag release algorithm should be robust against the statistical deviations which are inherent to experimental crash test data. Deterministic optimization algorithms cannot be used for the side aribag release algorithm since the objective function cannot be expressed in a closed form. From this background, genetic algorithm has been used for the optimization. The optimization requires moderate amount of computation and gives satisfactory results.