• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1403-1413
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• 2014

Structural optimization is widely accepted in industrial fields. Structural optimization pursues improved performance of the structures. Recently, structural optimization is actively utilized due to the well-developed commercial design software systems. Three popular commercial structural optimization systems are investigated and compared. They are MSC.Nastran, Genesis and OptiStruct. The performance of the systems is analyzed based on the quality of the optimum solution and the computational time. Linear static response size, shape and topology optimizations are explored and compared with some test examples. For fair comparison, the systems are run in the same environment and the optimization parameters affecting the performance are unified. The optimization results are analyzed and the performances and characteristics of each software system are discussed.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.182-191
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• 2011

Genetic algorithms (GA) and particle swarm optimization (PSO) are the most famous optimization techniques among various modern heuristic optimization techniques. These two approaches identify the solution to a given objective function, but they employ different strategies and computational effort; therefore, a comparison of their performance is needed. This paper presents the application and performance comparison of the PSO and GA optimization techniques for a static synchronous series compensator-based controller design. The design objective is to enhance power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem, and both PSO and GA optimization techniques are employed to search for the optimal controller parameters.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• The KSFM Journal of Fluid Machinery
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• v.14 no.5
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• pp.63-68
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• 2011

This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

• Journal of Information Technology Services
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• v.4 no.2
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• pp.125-133
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• 2005

Because of paradigm change to web service, numerous institutes have been suggested supporting solution about web service, and actively developed system using web service but it is hard to find out a systematic study for web service performance enhancement. Generally, there are SOAP message processing improvement and configuration optimization of server viewpoint for web service performance enhancement. Web service performance enhancement through SOAP message processing improvement have been studied related research but configuration optimization of server is hard to find out a systematic tuning model and performance criteria. In this paper, I suggested performance testing based tuning model and criteria of configuration optimization of server viewpoint. We executed practical analysis using tuning model about web service in internet. This paper show that the proposed tuning model and performance criteria is applicable to web service performance enhancement.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.4
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• pp.434-443
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• 2014

A turbo fan engine performance analysis and the optimization using particle swarm optimization(PSO) algorithm have been conducted to investigate the effects of major performance design parameters of an aircraft gas turbine engine. The FJ44-2C turbofan engine, which is widely used in the small business jet, CJ2 has been selected as the basic model. The design parameters consists of the bypass ratio, burner exit temperature, HP compressor ratio, fan inlet mass flow, and nozzle cooling air ratio. The sensitivity analysis of the parameters has been evaluated and the optimization of the parameters has been performed to achieve high net thrust or low specific fuel consumption.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.691-700
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• 2007

This paper proposes a simple but effective design method of PID control using a numerical optimization method. In order to achieve both stability and performance, gain and phase margins and performance indices of step response directly compose of the cost function. Hence, the proposed approach is a multiobjective optimization problem. The main effectiveness of this approach results from the strong capability of the used optimization method. A one-dimensional example concerning gain margin illustrates the practical applicability of the optimization method. The present approach has many degrees of freedom in controller design by only adjusting related weight constants. The attained PID controller is compared with Wang#s and Ho#s methods, IAE, and ISE for a high-order process, and the simulation result for various design targets shows that the proposed approach achieves desired time-domain performance with a guarantee of frequency-domain stability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.58-68
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• 2010

Particle Swarm Optimization (PSO) which has been well known to solve continuous problems can be applied to discrete combinatorial problems. Several DPSO (Discrete Particle Swarm Optimization) algorithms have been proposed to solve discrete problems such as traveling salesman, vehicle routing, and flow shop scheduling problems. They are different in representation of position and velocity vectors, operation mechanisms for updating vectors. In this paper, the performance of 5 DPSOs is analyzed by applying to traditional Traveling Salesman Problems. The experiment shows that DPSOs are comparable or superior to a genetic algorithm (GA). Also, hybrid PSO combined with local optimization (i.e., 2-OPT) provides much improved solutions. Since DPSO requires more computation time compared with GA, however, the performance of hybrid DPSO is not better than hybrid GA.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.56-68
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• 2012

Nowadays, Unmanned Combat Air Vehicle(UCAV) has become an important aircraft system for the national defense. For its efficiency and survivability, shape optimization of UCAV is an essential part of its design process. In this paper, shape optimization of UCAV was processed for aerodynamic performance improvement and Radar Cross Section(RCS) reduction using Multi Objective Genetic Algorithm(MOGA). Lift and induced drag, friction drag, RCS were calculated using panel method, boundary layer theory, Physical Optics(PO) approximation respectively. In particular, calculation applied Radar Absorbing Material(RAM) was performed for the additional RCS reduction. Results are indicated that shape optimization is performed well for improving aerodynamic performance, reducing RCS. Further study will be performed with higher fidelity tools and consider other design segments including structure.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.45-52
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• 2024

This paper introduces an approach to enhance the performance of magnetic manipulation systems for microrobot actuation. A variety of eight-electromagnet configurations have been proposed to date. The previous study revealed that achieving 5 degrees of freedom (5-DOF) control necessitates at least eight electromagnets without encountering workspace singularities. But so far, the research considering the influence of iron cores embedded in electromagnets has not been conducted. This paper offers a novel approach to optimizing electromagnet configurations that effectively consider the influence of iron cores. The proposed methodology integrates probabilistic optimization with finite element methods (FEM), using Bayesian Optimization (BO). The Bayesian optimization aims to optimize the worst-case magnetic force generation for enhancing the performance of magnetic manipulation system. The proposed simulation-based model achieves approximately 20% improvement compared to previous systems in terms of actuation performance. This study has the potential for enhancing magnetic manipulation systems for microrobot control, particularly in medical and microscale technology applications.