• Journal of the Korean Society for Precision Engineering
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• v.26 no.3
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• pp.129-136
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• 2009

The estimation of muscle force is important to understand the roles of the muscles. The static optimization method can be used to figure out the individual muscle forces. However, muscle forces during the movement including muscle co-contraction cannot be considered by the static optimization. In this study, a hybrid static optimization method was introduced to find the well-matched muscle forces with EMG signals under muscle co-contraction conditions. To validate the developed algorithm, the 3D motion analysis and its corresponding inverse dynamics using the musculoskeletal modeling software (SIMM) were performed on heel-rise movements. Results showed that the developed algorithm could estimate the acceptable muscle forces during heel-rise movement. These results imply that a hybrid numerical approach is very useful to obtain the reasonable muscle forces under muscle co-contraction conditions.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.89-97
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• 2021

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.753-760
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• 1994

This paper proposes a new method to compute the static thrust of a hybrid-type LPM by the coenergy method, which can be applied to a nonlinear programming of the optimization techniques for the optimal design. In the process of the computation, the magnetic nonlinearities of the permanent magnet, the primary and the secondary core are interpolated by the cubic spline method. And then, the equivalent magnetic circuit including the airgap reluctance which is a function of the displacement is modelled by the permeance method. The static thrust which is a derivative of the coenergy is computed by the Newton Raphson method at each displacement. To verify this proposed method, the results of the compjutation are compaction with those of the experiment obtained from the DLPM with 2 phase and 4 poles.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1315-1325
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• 2019

Aiming at the negative sequence and harmonic problems in the operation of railway static power conditioners, an optimization compensation strategy for negative sequence and harmonics is studied in this paper. First, the hybrid RPC topology and compensation principle are analyzed to obtain different compensation zone states and current capacities. Second, in order to optimize the RPC capacity configuration, the minimum RPC compensation capacity is calculated according to constraint conditions, and the optimal compensation coefficient and compensation angle are obtained. In addition, the voltage unbalance ${\varepsilon}_U$ and power factor requirements are satisfied. A PSO (Particle Swarm Optimization) algorithm is used to calculate the three indexes for minimum compensating energy. The proposed method can precisely calculate the optimal compensation capacity in real time. Finally, MATLAB simulations and an experimental platform verify the effectiveness and economics of the proposed algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1391-1407
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• 1990

In this paper, optimization procedures are presented considering the static and dynamic constraints for laminated composite plate and hybrid laminated composite plate subject to concentrated load on center of the plates. Design variables for this problem are ply angle or ply thickness. Deflection, natural frequency and specific damping capacity are considered as constraints. Using a recursive linear programming method, the nonlinear optimization problems are solved. By introducing the design scaling factor, the number of iterations is reduced significantly. Composite plates could be designed optimally combined with FEM analysis under various conditions. In the optimization procedure, verification for both analysis and design of the laminated composite plates are compared with the results of the others. Various design results are presented for the laminated composite plates and hybrid laminated composite plates.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.4
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• pp.436-443
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• 2015

In order to develop the PHEV(plug-in hybrid electric vehicle), the specific power transmission systems considering the PHEV system characteristics should be applied. A PHEV applied to series-parallel type hybrid power transmission system is a typical example. In this paper, the novel hybrid power systems are proposed by analyzing the existing PHEV system. The backward simulation program is developed to analyze the fuel efficiency of hybrid power system. Quasi-static models for each components such as engine, motor, battery and vehicle are included in the developed simulation program. To obtain an optimal condition for hybrid systems, an optimization approach called the dynamic programming is applied. The simulation is performed in various driving cycles. A weakness for the existing system is found through the simulation. To compensate for a discovered weakness, novel hybrid power systems are proposed by adding or moving the clutch to the existing system. Comparing the simulation results for each systems, the improved fuel efficiency for proposed systems are verified.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1827_1828
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• 2009

In this paper proposes a new algorithm for path planning using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the features of the ant colony algorithm method and the Maklink graph method. At first, paths are produced for a mobile robot in a static environment, and then, the midpoints of each obstacles nodes are found using the Maklink graph method. Finally, the shortest path is selected by the ant colony optimization algorithm.

• Smart Structures and Systems
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• v.11 no.1
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• pp.69-86
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• 2013

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.