• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.428-432
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• 2003

Quantitative Feedback Theory (QFT) is one of most effective methods of robust controller design and can be considered as a suitable method for systems with parametric uncertainties. Particularly it allows us to obtain controllers less conservative than other methods like $H_{\infty}$ and ${\mu}$-synthesis. In QFT method, we transform all the uncertainties and desired specifications to some boundaries in Nichols chart and then we have to find the nominal loop transfer function such that satisfies the boundaries and has the minimum high frequency gain. The major drawback of the QFT method is that there is no effective and useful method for finding this nominal loop transfer function. The usual approach to this problem involves loop-shaping in the Nichols chart by manipulating the poles and zeros of the nominal loop transfer function. This process now aided by recently developed computer aided design tools proceeds by trial and error and its success often depends heavily on the experience of the loop-shaper. Thus for the novice and First time QFT user, there is a genuine need for an automatic loop-shaping tool to generate a first-cut solution. In this paper, we approach the automatic QFT loop-shaping problem by using an algorithm involving Linear Programming (LP) techniques and Genetic Algorithm (GA).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Speech Sciences
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• v.15 no.4
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• pp.85-96
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• 2008

Automatic speech recognition has severe performance degradation under noisy environments. To cope with the noise problem, many methods have been proposed. Most of them focused on noise-robust features or model adaptation. However, researchers have overlooked utterance verification (UV) under noisy environments. In this paper we discuss UV problems based on the normalized confidence measure. First, we show that UV performance is also degraded in noisy environments with the experiments of an isolated word recognition. Then we observe how the degradation of UV performances is suffered. Based on the UV experiments we propose a modeling method of the statistics of phone confidences using sigmoid functions. For obtaining the parameters of the sigmoidal models, the particle swarm optimization (PSO) is adopted. The proposed method improves 20% rejection performance. Our experimental results show that the PSO-NCM can apply noise speech recognition successfully.

• Proceeding of KASS Symposium
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• 2006.05a
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• pp.191-204
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• 2006

This paper investigate the optimum thickness distribution of plate structure with different essential boundary conditions in the fundamental natural frequency maximization problem. In this study, the fundamental natural frequency is considered as the objective function to be maximized and the initial volume of structures is used as the constraint function. The computer-aided geometric design (CAGD) such as Coon's patch representation is used to represent the thickness distribution of plates. A reliable degenerated shell finite element is adopted calculate the accurate fundamental natural frequency of the plates. Robust optimization algorithms implemented in the optimizer DoT are adopted to search optimum thickness values during the optimization iteration. Finally, the optimum thickness distribution with respect to different boundary condition

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.112-120
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• 2011

The early phase of design intrinsically contains multiple sources of uncertainty in describing design, and nevertheless the decision-making process at this phase exerts a critical effect upon drawing a successful design. This paper proposes a set-based design approach for multi-objective design problem under uncertainty. The proposed design approach consists of four design processes including set representation, set propagation, set modification, and set narrowing. This approach enables the flexible and robust design while incorporating designer's preference structure. In contrast to existing optimization techniques, this approach generates a ranged set of design solutions that satisfy changing sets of performance requirements.

• Journal of Drive and Control
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• v.20 no.4
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.

• Journal of Ocean Engineering and Technology
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• v.27 no.1
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• pp.85-92
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• 2013

This paper deals with the resonant type of a WEC (wave energy converter) and the determination method of its geometric parameters which were obtained to construct the robust and optimal structure, respectively. In detail, the optimization problem is formulated with the constraints composed of the response surfaces which stand for the resonance period(heave, pitch) and the meta center height of the buoy. Use of a signal-to-noise ratio calculated from normalized multi-objective results with the weight factor can help to select the robust design level. In order to get the sample data set, the motion responses of the power buoy were analyzed using the BEM (boundary element method)-based commercial code. Also, the optimization result is compared with a robust design for a feasibility study. Finally, the power efficiency of the WEC with the optimum design variables is estimated as the captured wave ratio resulting from absorbed power which mainly related to PTO (power take off) damping. It could be said that the resultant of the WEC design is the economical optimal design which satisfy the given constraints.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.117-123
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• 2003

Rotational machines such as optical disk drives, hard disk drives, and so on are subject to periodic disturbances caused by their mechanical characteristics. In the meanwhile, it is well known that repetitive control rejects periodic disturbance effectively. This paper presents a practical application of repetitive control to the track-following servo of an optical disk drive. The repetitive control system is composed of two repetitive controllers which compensate for periodic disturbances generated by track geometry and eccentric rotation of disk and a feedback controller stabilizing the feedback loop. A robust stability for all plant uncertainties is proved using linear matrix inequalities (LMIs). In the controller design, a weighting function is introduced for the feedback controller to ensure a minimum loop gain and a sufficient phase margin. The repetitive controllers and the feedback controller are designed by solving an optimization problem which can consider the robust stability condition and the system performance. The developed repetitive control system is implemented in the digital control system with a 16-bit fixed-point digital signal processor (DSP). Through simulation and experiment. The feasibility of the proposed repetitive control system is verified.

• Structural Engineering and Mechanics
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• v.62 no.6
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• pp.709-717
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• 2017

This paper develops a two-stage method for structural damage identification by using modal data. First, the Residual Force Vector (RFV) is introduced to detect any potentially damaged elements of structures. Second, data of the frequency domain are used to build up the objective function, and then the Imperialist Competitive Algorithm (ICA) is utilized to estimate damaged extents. ICA is a heuristic algorithm with simple structure, which is easy to be implemented and it is effective to deal with high-dimension nonlinear optimization problem. The advantages of this present method are: (1) Calculation complexity can be decreased greatly after eliminating many intact elements in the first step. (2) Robustness, ICA ensures the robustness of the proposed method. Various damaged cases and different structures are investigated in numerical simulations. From these results, anyone can point out that the present algorithm is effective and robust for structural damage identification and is also better than many other heuristic algorithms.

• Computational Structural Engineering
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• v.9 no.3
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• pp.179-186
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• 1996

A simple nonlinear programming(NLP) formulation for the optimal topology problem of structures is developed and examined. The NLP formulation is general, and can handle arbitrary objective functions and arbitrary stress, displacement constraints under multiple loading conditions. The formulation is based on simultaneous analysis and design approach to avoid stiffness matrix singularity resulting from zero sizing variables. By embedding the equilibrium equations as equality constraints in the nonlinear programming problem, we avoid constructing and factoring a system stiffness matrix, and hence avoid its singularity. The examples demonstrate that the formulation is effective for finding an optimal solution, and shown to be robust under a variety of constraints.