• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.510-512
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• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.643-645
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• 1999

In between of linear and nonlinear systems lies a large class of bilinear systems. The major importance of bilinear systems lies in the applications to the real world systems such as many physical processes, many biological process, some economic process. Despite vast application of bilinear systems they have not been studied extensively in the domain of singularly perturbations except for a few minor results. In this paper we will utilize singular peturbations theory to obtain the closed-loop optimal solution for discrete-time bilinear systems.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.1002-1004
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• 1999

The aim of this paper is to suggest a design method of the optimal multivariable $H_{\infty}$ control system using genetic algorithm(GA). This $H_{\infty}$ control system is designed by applying GA to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. The effectiveness of this $H_{\infty}$ control system is verified by nonlinear simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.90-98
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• 2015

In this paper, an advanced teaching-learning based optimization(TLBO) method for the magnetic levitation controller of Maglev transportation system is proposed to optimize the control performances. An attraction-type levitation system is intrinsically unstable and requires a delicate control. It is difficult to completely satisfy the desired performance through the methods using conventional methods and intelligent optimizations. In the paper, we use TLBO and clonal selection algorithm to choose the optimal control parameters for the magnetic levitation controller. To verify the proposed algorithm, we compare control performances of the proposed method with the genetic algorithm and the particle swarm optimization. The simulation results show that the proposed method is more effective than conventional methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.336-340
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• 1997

For optimal design of micro stage, we were measured to displacement of piezo-electric transducer that was based on voltage value. And then researchers were analyzed to microstage through FEM with displacement data including voltage value of piezo-electric transducer. For verification of analyzing results, we were gauged on displacement by using Laser-interferometer. And researchers were confirmed to propriety of micro stage design with FEM, were obtained error rate that are 3.5% between measurement results and analyzing results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1670-1679
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• 1995

In this paper, an optimal variable structure controller with a multilayer neural inverse identifier is proposed. A multilayer neural network with error back propagation learning algorithm is used for construction the neural inverse identifier which is an observer of the external disturbances and the parameter variations of the system. The variable structure controller with the multilayer neural inverse identifier not only needs a small part of a priori knowledge of the bounds of external disturbances and parameter variations but also alleviates the chattering magnitude of the control input. Also, an optimal sliding line is designed by the optimal linear regulator technique and an integrator is introduced for solving the reaching phase problem. Computer simulation results show that the proposed approach gives the effective control results by reducing the chattering magnitude of control input.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.25 no.4
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• pp.209-213
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• 1989

The author suggested control method of partial cavitation with electro-magnetic accelerator and showed that the cavity shape decreased with this suggestion which compared with the theoretical ones. Using the cavity flow method proposed by the author in this paper, it is predicted that cavitation volume of the shape is less than the previous type one. Comparisons were performed in order to verify these facts, using both shape which calculated by the method. It was found that the difference of cavitation performance between the two shape of volume were decreased, because of the new method accelerated of flow more than previous theoretical ones.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.104-106
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• 2007

In this paper, we propose an approach to design of optimized Cascade controller for Rotary Inverted Pendulum system using Hierarchical Fair Competition-based Genetic Algorithm(HFCGA). GAs may get trapped in a sub-optimal region of the search space thus becoming unable to find better quality solutions, especially for very large search space. The Parallel Genetic Algorithms(PGA) are developed with the aid of global search and retard premature convergence. HFCGA is a kind of multi-populations of PGA. In this paper, we design optimized Cascade controller by HFCGA for Rotary Inverted Pendulum system that is nonlinear and unstable. Cascade controller comprise two feedback loop, parameters of controller optimize using HFCGA. Then designed controller evaluate by apply to the real plant.

• Journal of Advanced Marine Engineering and Technology
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• v.11 no.3
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• pp.61-69
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• 1987

The PID controller is one of the most popular devices for control systems and the adjustment of its parameters has been generally accomplished by semi-empirical rules and has been considered only in the view of improvement of the control performance. But in modern control theory, a quadratic form is introduced as a criterion function which considers not only to improve quality of control but also to save energy required for the control. In this paper, authors propose a method of the parameter adjustment of the PID controller by means of maximum principle minimizing the quadratic criterion function and establish a link between the conventional parameter adjustment method and the technique of the modern optimal control theory in the design of a PID controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.560-567
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• 2000

A soft-switching PFC-Inverter for using AC motor drive such as the inverter air-conditioner with single phase medium size is proposed. In order to improve the power factor and the efficiency, in this paper, the ZVT topoloty in the conventional PFC-Inverter is adopted. So, the operation mode of the proposed ZVT PFC-Inverter is analyzed and the optimum circuit is designed. At last, the PSPICE, PSIM simulation and experiment results are presented in order to verify the validity of the proposed circuit.