• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.652-654
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• 1995

This paper proposes a design of self-tuning fuzzy controller based on evolutionary computation. Optimal membership functions are round by using evolutionary computation. Genetic algorithms and evolution strategy are used for tuning of fuzzy membership function. A arbitrarily speed trajectories is selected to show the performance of the proposed methods. Simulation results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on evolutionary computation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.678-690
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• 2014

The current networks do not disclose information about a management domain due to scalability, manageability and commercial reasons. Therefore, it is very hard to calculate an optimal path to the destination. Also, due to poor information sharing, if an error occurs in the intermediate path, it is very difficult to re-search the path and find the best path. Hence, to manage each domain more efficiently, an architecture with top-level path computation node which can obtain information of separate nodes are highly needed This study aims to investigate a federation of a united network around NRN(National Research Network) that could allow resource sharing between countries and also independent resource management for each country. Considering first the aspects that can be accessed from the perspective of a national research network, ICE(Information Control Element) and GFO(Global Federation Organizer)-based architecture is designed as a top-level path computation element to support traffic engineering and applied to the multi-domain network. Then, the federation for the independent management of resources and resource information sharing among national research networks have been examined.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.37-42
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• 2006

The voltage drop in electrical circuits causes a heat accumulation of wiring. This heat could change the specific character of an insulator and deteriorate the dielectric strength so that it could affect an electric leakage, an electric ant a power failure and a fire caused by the short circuit. Therefore optimal design for voltage drop in electrical wiring became an important factor to ensure the safety and economical efficiency of electrical facilities. So in this paper, I analyzed consequences that voltage drop affects in electrical wiring in multi-distributed system used for low electrical system such as road lights, Building, subway station which needs securities for the public society. And I proposed voltage drops computation program and optimal design to ensure the safety and economical efficiency.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.9
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• pp.457-460
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• 2005

This paper proposes a new Interior Point Method algorithm to improve the computation speed and solution stability, which have been challenging problems for employing the nonlinear Optimal Power Flow. The proposed algorithm is different from the tradition Interior Point Methods in that it adopts the Predictor-Corrector Method. It also accommodates the five minute dispatch, which is highly recommenced in modern electricity market. Finally, the efficiency and applicability of the proposed algorithm is demonstrated with a case study.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1193-1196
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.118-123
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• 1989

This work deals with fast-to-compute global control laws for time-optimal motion of strongly nonlinear dynamic systems like resolute robots. the theory of cell-to-cell mappings for dynamical systems offer the possibility of doing the vast majority of the control law computation offline in case of time optimization with constrained inputs. These cells result from a coarse discretization of likely swaths of state space into a set of nonuniform, contiguous volumes of relatively simple shapes. Once the cells have been designed, the bang-bang schedules for the inputs are determined for all likely starting cells and terminating cells. the resulting control law is an open-loop optimal control law with feedback monitoring and correction.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.748-752
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• 1991

Tree network consisting of communicating processors is considered. The objective is to minimize the computation time by distributing the processing load to other nodes. The effect of the order of load distribution on the processing time is addressed. An algorithm which optimally determines the order of load distribution is developed. It is shown that the order depends only on the channel capacity between nodes but not on the computing capability of each node.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.501-504
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• 2003

This paper presents a new fractal coding scheme to find more optimal transformation by estimation of the optimal attractor. The conventional fractal coding schemes based on the collage theorem obtain the transformation to minimize the distance between an original image and its collage image. Heavy computation is why the schemes widely adopt the theorem. In other words, the optimal transformation can be obtained after the attractors of all the possible transformations are generated and then compared with an original image. It is clear that this process is not practical. Therefore, we introduce a sub-optimal scheme that provides better transformation than the conventional scheme, relieving the complexity problem in the optimal transformation. In a simple case, the optimal transformation can be obtained considering all the attractors and then our scheme is compared with the optimal. In general cases not to be able to find the optimal, our scheme is also evaluated and compared with the conventional schemes.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.111-119
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• 1996

In this paper, we propose time-optimal trajectory planning algorithms for cooperative multi-robot manipulators system considering optimal load distribution. Internal forces essentially effect on time optimal trajectory planning and if they are comitted, the time optimal scheme is not no longer true. Therefore, we try to find the internal force factors of cooperative robot manipulators system in a time-optimal aspect. In this approach, a specific generalized inverse is used and is fuzzified for the purpose. In this optimal method, the fuzzy logic concept is used and selected for diminishing computation time, for finding the load distribution factors.