• Journal of applied mathematics & informatics
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• v.7 no.3
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• pp.887-894
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• 2000

In this paper we consider the corrected version of the algorithm of the state-minimization for the nondeterministic finite automata: we correct here a mistake of the previous paper, where the same problem was considered.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.379-392
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• 1999

The problem of the state-minimization for the nonde-terministic finite Rabin-Scott's automata is considered. A new algo-rithm for this problem is obtained. The obtained algorithm has the exponential effectiveness like the earlier-known algorithms for this problem. But each of previous algo-rithms amounts to the search of minimum generative system for local reaction of equal automaton of canonical form and unlike them we use in this paper two special function marking states of the given automaton.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.127-136
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• 1989

A Symbolic cover Minimization Algorithm and State CHDL Description for Finite State Machine Synthesizer are Presented. State CHDL are used for design of PLA based finite state machine, also the symbolic cover minimization algorithms are based upon single cube containment and distance 1 merging algorithms. The procedure for state machine synthesizer has been applied to practical example, including traffic light controller by using Boulder Optimal Logic Design System.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1477-1480
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• 1997

This paper is concerned with the design of a suboptimal robust Kalman filter using LMI approach for system models in the state space, which are subjected to parameter uncertainties in both the state and measurement atrices. Under the assumption that augmented system composed of the uncertain system and the state estimation error dynamics should be stable, a Lyapunov inequality is obtained. And from this inequaltiy, the filter design problem can be transformed to the gneric LMI problems i.e., linear objective minimization problem and generalized eigenvalue minimization problem. When applied to uncertain linear system modles, the proposed filter can provide the minimum upper bound of the estimation error variance for all admissible parameter uncertainties.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.693-703
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• 2001

In this paper we consider non-deterministic finite Rabin-Scott’s automata. We use a special structure to descibe all the possible edges of non-determinstic finite automaton defining the given regular language. Such structure can be used for solving various problems of finite automata theory. One of these problems is edge-minimization of non-deterministic automata. As we have not touched this problem before, we obtain here two versions of the algorithm for solving this problem to continue previous series of articles.

• KIEE International Transactions on Power Engineering
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• v.12A no.1
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• pp.31-35
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• 2002

This paper presents a new operation scheme of UPFC to minimize both generation costs and active power losses in a normal operation state of power system. In a normal operation, cost minimization is a matter of primary concern among operating objectives. This paper considers two kinds of costs, generation costs and transmission losses. The total generation cost of active powers can be minimized by optimal power flow, and active power losses in the transmission system can be also minimized by power flow control of UPFC incorporated with minimization of generation costs. In order to determine amounts of active power reference of each UPFC required for the cost minimization, an iterative optimization algorithm based on the power flow calculation using the decoupled UPFC model is proposed. For verification of the proposed method, intensive studies have been performed on a 3-unit 6-bus system equipped with a UPFC.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.103-116
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• 2003

States explosion due to composition of spaces of data, temporal, and locational values is one of the well-known critical problems which cause difficulty in understanding and analysing real-time systems specified with state-based formal methods. In order to overcome this problem, this paper presents an abstraction method for state minimization based on an abstraction in system specification and an abstraction in system execution. The first is named the syntactic in system specification and an abstraction in system execution. The first is named the syntactic abstraction, through which the patterns of the unconditionally internalized computation and the repetition and selection structures are abstracted. The latter is named the semantic abstraction, through which the patterns of the execution space represented with data. Through the abstractions, the components of a system in specification and execution model is hierarchically organized. The system can be analyzed briefly in the upper level in an skeleton manner with low complexity. The system, however, can be abstraction method for the state minimization and the decrease in analysis complexity through the abstraction with examples.

• Korean Journal of Crystallography
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• v.11 no.3
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• pp.173-175
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• 2000

Computational technique, based on the minimization of the crystal energy with respect to atomic coordinates, are shown to reproduce successfully complex crystal structure, in this case, strontium hexaaluminate magnetoplumbite, SrAl/sub 12/O/sub 19/. The experimental crystal structure and symmetry of the complex material is well reproduced with our potential models and some crystal physical properties are calculated.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.425-436
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• 2016

In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.660-667
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• 2003

In this study, a Multiple Objective Mixed Integer Programming (MOMIP) Model is developed for sewer rehabilitation planning by considering cost, inflow/infiltration. A sewer rehabilitation planning model is required to decide the economic life of the sewer by considering trade-off between cost and inflow/infiltration. And it is required to find the optimal rehabilitation timing, according to the cost effectiveness of each sewer rehabilitation within the budget. To develop such a model, a multiple objective mixed integer programming model is formulated based on network flow optimization. The network is composed of state nodes and arcs. The state nodes represent the remaining life and the arcs represent the change of the state. The model consider multiple objectives which are cost minimization and minimization of inflow/infiltration. Using the multiple objective optimization, the trade-off between the cost and inflow/infiltration is presented to the planner so that a proper sewer rehabilitation plan can be selected.