• Journal of Information Technology Services
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• v.10 no.3
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• pp.167-177
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• 2011

Code obfuscation is a technique that protects the abstract data contained in a program from malicious reverse engineering and various obfuscation methods have been proposed for obfuscating intention. As the abstract data of control flow about programs is important to clearly understand whole program, many control flow obfuscation transformations have been introduced. Generally, inlining is a compiler optimization which improves the performance of programs by reducing the overhead of calling invocation. In code obfuscation, inlining is used to protect the abstract data of control flow. In this paper, we define new control flow complexity metric based on entropy theory and N-Scope metric, and then apply genetic algorithm to obtain optimal inlining results, based on the defined metric.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.556-559
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• 2007

The notion of linearity is fundamental in science and engineering. Much of system and control theory is based on the analysis of linear system, which does not care whether it is nonlinear and complex. The dynamic programming is one of concerned technology when users are interested in choosing best choice from system operation for nonlinear or dynamic system‘s performance and control problem. In this paper, we will introduce the dynamic programming which is based on discrete system. When the discrete system is constructed with discrete state, transfer between states, and the event to induct transfer, the discrete system can describe the system operation as dynamic situation or symbolically at the logical point of view. We will introduce technologies which are related with controllable of Controlled Markov Chain as shown example of simple game. The dynamic programming will be able to apply to optimal control part which has adaptable performance in the discrete system.

• Journal of Mechanical Science and Technology
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• v.15 no.6
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• pp.776-787
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• 2001

The turbofan engine performance analysis for a medium scale commercial aircraft was carried out and the LQR control scheme for performance optimization was studied. By using scaled component maps from well-known CF6 engine characteristics, the steady-state performance analysis result was compared with BR715-56 engine performance data. The transient performance analysis was performed with four fuel schedules. The linear simulation was done at the maximum take-off condition. The real time linear simulation was performed by interpolation of the system matrices, which used the least square method as the function of LPC rotational speed. By using linear system matrices of design point, the LQR controller which used control variables for the fuel flow and the LPC bleed air was designed.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.1-7
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• 2008

Superconducting Magnetic Energy Storage (SMES) can inject or absorb real and reactive power to or from a power system at a very fast rate on a repetitive basis. These characteristics make the application of SMES ideal for transmission grid control and stability enhancement. The purpose of this paper is to introduce the SMES model and scheme to control the active and reactive power through the power electronic device. Furthermore, an optimal priority scheme is proposed for the combination of active and reactive power control to be able to stabilize power transient swings.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.995-1002
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• 2000

In this paper, fuzzy logic controllers(FLC) are designed for control of flight. For tuning FLC, we used adaptive evolutionary algorithms(AEA) which uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. We used AEA to search for optimal settings of the membership functions shape and gains of the inputs and outputs of FLC. Finally, the proposed controller is applied to the high-angle-of-attack flight system for a supermaneuverable version of the f-18 aircraft and compares with other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.485-485
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• 2000

A design method of model following control system using neural networks is proposed. An unknown nonlinear single-input single-output plant is identified using a multilayer neural networks. A linear controller is designed fer the linear approximation model obtained by linearinzing the identification model. The identification model is also used as a plant emulator to obtain the prediction error. Deficient servo performance due to controlling nonlinear plant with only linear controller is mended by adjusting the linear controller output using the prediction output and the parameters of the identification model. An optimal preview controller is adopted as the linear controller by reason of having good servo performance lowering the peak of control input. Validity of proposed method is illustrated through a numerical simulation.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.2
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• pp.75-80
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• 2016

This study proposes a efficient technology to control the optimal trajectory planning and real-time implementation method which can perform autonomous travelling for unmaned factory automation. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on Route planning and control algorithm, we suggested representation of edge cost, heuristic function, and priority queue management, to make a modified Route planning algorithm. Performance of the proposed algorithm is verified by simulation test.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.600-602
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• 1995

The paper presents neural network control techniques for load frequency control of two area power system. Using learning algorithm of error back propagation after learning accept input on the optimal control $e_{i}$, $\dot{e}_{i}$, and $u_{i}$ frequency characteristic and tie-line load flow characteristic investigated dynamic. From result simulation, frequency deviation and tie-line load flow deviation have reduction remarkable.

• International Journal of Automotive Technology
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• v.6 no.5
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• pp.529-536
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• 2005

This paper presents a novel design of a fuzzy control strategy (FCS) based on torque distribution for parallel hybrid electric vehicles (HEVs). An empirical load-regulating vehicle operation strategy is developed on the basis of analysis of the components efficiency map data and the overall energy conversion efficiency. The aim of the strategy is to optimize the fuel economy and balance the battery state-of-charge (SOC), while satisfying the vehicle performance and drivability requirements. In order to accomplish this strategy, a fuzzy inference engine with a rule-base extracted from the empirical strategy is designed, which works as the kernel of a fuzzy torque distribution controller to determine the optimal distribution of the driver torque request between the engine and the motor. Simulation results reveal that compared with the conventional strategy which uses precise threshold parameters the proposed FCS improves fuel economy as well as maintains better battery SOC within its operation range.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.