• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.877-885
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• 2018

The anti-submarine helicopter is the most effective weapon system in anti-submarine warfare. Recently changes in the introduction of the anti-submarine warfare sonar system are expected to operate multi-static sonar equipment of the anti-submarine helicopter. Therefore, it is required to study the operational concept of multi-static of anti-submarine helicopter. This paper studies on the optimal search of multi-static based on anti-submarine helicopter considering Furthest On Circles(FOC). First, the deployment of the sensors of the anti-submarine helicopter is optimized using genetic algorithms. Then, the optimized model is extended to consider FOC. Finally, the proposed model is verified by comparing pattern-deployment the search method in Korean Navy.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.853-866
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• 2011

We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

• Journal of Agricultural Extension & Community Development
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• v.21 no.4
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• pp.1149-1189
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• 2014

Nowadays, many farmers use online management diagnosis tool developed by Rural development agency(RDA) for the purpose of self-diagnosis of their farm management. Database(DB) was created using the diagnosis results and has been used for agri-firm management consulting. However, the amount of diagnosis data in the DB has been decreasing year by year. This means that the diagnosis tool of RDA did not reach farmers' expectation. Therefore it is necessary to develop a practical consulting tool which is applicable for various types of agri-firm management. This study introduces a management diagnosis tool and consulting method based on multi-contingency organization theory and value chain model for the purpose of improving existing tools and methods. The consulting method based on multi-contingency organization theory shows the core strategy of agri-firms by two different ways such as "efficiency-oriented" direction and "effectiveness-orientated" direction. Also, this method emphasizes that the performance of firm can be achieved when subelements of firm activities follow the same direction with the orientation of core strategy. The important thing is the right firm management activity fitted to its strategic direction. Through this action, limited firm resources can be optimized. In order to make itself understand, this study shows a practical example applied by this method from actual agri-firms.

• Structural Engineering and Mechanics
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• v.65 no.2
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• pp.173-181
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• 2018

In this paper, finite element (FE) model updating based on multi-objective optimization with the surrogate model for a steel plate girder bridge is investigated. Conventionally, FE model updating for bridge structures uses single-objective optimization with finite element analysis (FEA). In the case of the conventional method, computational burden occurs considerably because a lot of iteration are performed during the updating process. This issue can be addressed by replacing FEA with the surrogate model. The other problem is that the updating result from single-objective optimization depends on the condition of the weighting factors. Previous studies have used the trial-and-error strategy, genetic algorithm, or user's preference to obtain the most preferred model; but it needs considerable computation cost. In this study, the FE model updating method consisting of the surrogate model and multi-objective optimization, which can construct the Pareto-optimal front through a single run without considering the weighting factors, is proposed to overcome the limitations of the single-objective optimization. To verify the proposed method, the results of the proposed method are compared with those of the single-objective optimization. The comparison shows that the updated model from the multi-objective optimization is superior to the result of single-objective optimization in calculation time as well as the relative errors between the updated model and measurement.

• Smart Structures and Systems
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• v.18 no.3
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• pp.569-584
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• 2016

This paper presents a method for stochastic modelling of fatigue crack growth and optimising inspection and maintenance strategy for the structural members of steel bridges. The fatigue crack evolution is considered as a stochastic process with uncertainties, and the Gamma process is adopted to simulate the propagation of fatigue crack in steel bridge members. From the stochastic modelling for fatigue crack growth, the probability of failure caused by fatigue is predicted over the service life of steel bridge members. The remaining fatigue life of steel bridge members is determined by comparing the fatigue crack length with its predetermined threshold. Furthermore, the probability of detection is adopted to consider the uncertainties in detecting fatigue crack by using existing damage detection techniques. A multi-objective optimisation problem is proposed and solved by a genetic algorithm to determine the optimised inspection and maintenance strategy for the fatigue affected steel bridge members. The optimised strategy is achieved by minimizing the life-cycle cost, including the inspection, maintenance and failure costs, and maximizing the service life after necessary intervention. The number of intervention during the service life is also taken into account to investigate the relationship between the service life and the cost for maintenance. The results from numerical examples show that the proposed method can provide a useful approach for cost-effective inspection and maintenance strategy for fatigue affected steel bridges.

• Smart Structures and Systems
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• v.20 no.1
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• pp.1-10
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• 2017

Ionic Polymer Metal Composite (IPMC) is an electroactive polymer (EAP) and a promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design, and lack of moving parts. Although widely used in industry, this material requires accurate numerical models and knowledge of optimal control methods. This paper presents State-Dependent Riccati Equation (SDRE) approach as one of rapidly emerging methodologies for designing nonlinear controllers. Additionally, the present paper describes a novel method of Multi HGO Observer design. In the proposed design, the calculated position of the IPMC strip accurately tracks the target position, which is illustrated by the experiments. Numerical results and comparison with experimental data are presented and the effectiveness of the proposed control strategy is verified in experiments.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.66-78
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• 2007

A multi-point aerodynamic shape optimization technique has been developed for helicopter rotor blades in hover based on a continuous adjoint method on unstructured meshes. The Euler flow solver and the continuous adjoint sensitivity analysis were formulated on the rotating frame of reference. The 'objective function and the sensitivity were obtained as a weighted sum of the values at each design point. The blade section contour was modified by using the Hicks-Henne shape functions. The mesh movement due to the blade geometry change was achieved by using a spring analogy. In order to handle the repeated evaluation of the design cycle efficiently, the flow and adjoint solvers were parallelized based on a domain decomposition strategy. A solution-adaptive mesh refinement technique was adopted for the accurate capturing of the wake. Applications were made to the aerodynamic shape optimization of the Caradonna-Tung rotor blades and the UH-60 rotor blades in hover.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.918-925
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• 2006

Medical robotics and computer aided surgery in general, and robotic telesurgery in particular, are promising applications of robotics. In this paper, we shows a novel single-master (PHANTOM based single-master multi-slave telerobotic system) multi-slave system using two parallel mechanism micromanipulators as a slave device. After a general introduction to the systems structure and configuration of telerobotic system, a manipulation control strategy to build the system that human and both manipulators perform the cooperative manipulation, is introduced, followed by its kinematic analysis, mapping method, and experimental results.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.218-223
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• 2008

A new Pareto-optimal design algorithm, requiring least computational work, is proposed for a single phase AC solenoid actuator with multi-design-objectives: maximizing holding force and minimizing eddy current loss simultaneously. In the algorithm, the design space is successively reduced by a suitable factor, as iteration repeats, with the center of pseudo-optimal point. At each iteration, the objective functions are approximated to a simple second-order response surface with the CCD sampling points generated within the reduced design space, and Pareto-optimal solutions are obtained by applying($1+{\lambda}$) evolution strategy with the fitness values of Pareto strength.

• Journal of Power Electronics
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• v.14 no.3
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• pp.499-506
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• 2014

This paper proposes a 3 kW single-phase bi-directional multi-level converter for energy storage applications. The proposed topology is based on the H-bridge structure with four switches connected to the DC-link. A simple phase opposition disposition PWM method that requires only one carrier signal is also suggested. The switching sequence to balance the capacitor voltage is considered. The topology can be extended to a nine-level converter or a three-phase system. The operating principle of the proposed converter is verified through a simulation and an experiment.