• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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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.

• 대한산업공학회지
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• 제19권2호
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• pp.3-13
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• 1993

In this study, we develop a B & B type algorithm for the concave minimization problem with 0-1 knapsack constraint. Our algorithm reformulates the original problem into the singly linearly constrained concave minimization problem by relaxing 0-1 integer constraint in order to get a lower bound. But this relaxed problem is the concave minimization problem known as NP-hard. Thus the linear function that underestimates the concave objective function over the given domain set is introduced. The introduction of this function bears the following important meanings. Firstly, we can efficiently calculate the lower bound of the optimal object value using the conventional convex optimization methods. Secondly, the above linear function like the concave objective function generates the vertices of the relaxed solution set of the subproblem, which is used to update the upper bound. The fact that the linear underestimating function is uniquely determined over a given simplex enables us to fix underestimating function by considering the simplex containing the relaxed solution set. The initial containing simplex that is the intersection of the linear constraint and the nonnegative orthant is sequentially partitioned into the subsimplices which are related to subproblems.

• 한국도로학회논문집
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• 제17권5호
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• pp.93-103
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• 2015

PURPOSES : The purpose of this study is to present a linear programing optimization model for the design of lane-based lane-uses and signal timings for an isolated intersection. METHODS: For the optimization model, a set of constraints for lane-uses and signal settings are identified to ensure feasibility and safety of traffic flow. Three types of objective functions are introduced for optimizing lane-uses and signal operation, including 1) flow ratio minimization of a dual-ring signal control system, 2) cycle length minimization, and 3) capacity maximization. RESULTS : The three types of model were evaluated in terms of minimizing delay time. From the experimental results, the flow ratio minimization model proved to be more effective in reducing delay time than cycle length minimization and capacity maximization models and provided reasonable cycle lengths located between those of other two models. CONCLUSIONS : It was concluded that the flow ratio minimization objective function is the proper one to implement for lane-uses and signal settings optimization to reduce delay time for signalized intersections.

• Advances in Energy Research
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• 제4권4호
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• pp.255-274
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• 2016

This paper presents a novel symbiotic organisms search (SOS) algorithm to optimize both real power loss (RPL) and voltage stability limit (VSL) of a transmission network by controlling the variables such as unified power flow controller (UPFC) location, UPFC series injected voltage magnitude and phase angle and transformer taps simultaneously. Mathematically, this issue can be formulated as nonlinear equality and inequality constrained multi objective, multi variable optimization problem with a fitness function integrating both RPL and VSL. The symbiotic organisms search (SOS) algorithm is a nature inspired optimization method based on the biological interactions between the organisms in ecosystem. The advantage of SOS algorithm is that it requires a few control parameters compared to other meta-heuristic algorithms. The proposed SOS algorithm is applied for solving optimum control variables for both single objective and multi-objective optimization problems and tested on New England 39 bus test system. In the single objective optimization problem only RPL minimization is considered. The simulation results of the proposed algorithm have been compared with the results of the algorithms like interior point successive linear programming (IPSLP) and bacteria foraging algorithm (BFA) reported in the literature. The comparison results confirm the efficacy and superiority of the proposed method in optimizing both single and multi objective problems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.744-746
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• 2000

This paper presents an optimum design of a linear induction motor(LIM) using genetic algorithm(GA). Sequential unconstrained minimization technique(SUMT) is used to transform the nonlinear optimization with constraints to a simple unconstrained problem. The objective functions of LIM such as trust, weight are optimized and the result was applied to the design of linear induction pump.

• ETRI Journal
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• 제6권4호
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• pp.31-36
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• 1984

This paper presents an efficient method for real power loss minimization and for improvements in voltage profiles. This method is accomplished by optimal control of reactive power in the system. The problem is formulated as an optimization problem, suitable for solution by linear programming technique. After establishing the objective function for minimizing the system losses with the help of linearised sensitivity relationships of control variables, i. e., the transformer tap position, generator terminal voltages and switchable reactive power sources. The linear programming technique is used to determine the optimal adjustments to the above variables, simultaneously satisfying the constraints. The proposed algorithm has been tested on a sample system and the result is presented and discussed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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• pp.220-223
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• 2003

This paper presents VSCOPF(Votage Stability Constrained Optimal Power Flow) algorithm based on SLP(Successive Linear Programming) to interpret the large scale system. Voltage stability index used to this paper is L index to be presented by function form. The objective function consists of load shedding cost minimization. Voltage stability indicator constraint was incorporated in traditional OPF formulation. as well as the objective function and constraints are linearlized and the optimal problem is performed by SLP(Successive Linear Programming). In this paper, the effect of voltage stability limit constraint is showed in the optimal load curtailment problems. As a result, an optimal solution is calculated to minimize load shedding cost guaranteeing voltage security level. Numerical examples using IEEE 39-bus system is also presented to illustrate the capabilities of the proposed formulation.

• Journal of applied mathematics & informatics
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• 제14권1_2호
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• pp.97-113
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• 2004

In this paper we shall study moving boundary problems, and we introduce an approach for solving a wide range of them by using calculus of variations and optimization. First, we transform the problem equivalently into an optimal control problem by defining an objective function and artificial control functions. By using measure theory, the new problem is modified into one consisting of the minimization of a linear functional over a set of Radon measures; then we obtain an optimal measure which is then approximated by a finite combination of atomic measures and the problem converted to an infinite-dimensional linear programming. We approximate the infinite linear programming to a finite-dimensional linear programming. Then by using the solution of the latter problem we obtain an approximate solution for moving boundary function on specific time. Furthermore, we show the path of moving boundary from initial state to final state.

• 산업경영시스템학회지
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• 제20권43호
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• pp.139-144
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• 1997

The objective of this study is to establish an actual optimization strategy for the traditional multi-stage distribution system which consists of factory warehouse, central distribution warehouse, and regional distribution warehouse under the basic assumption of distribution system. A minimization algorithm of total operating cost in a multi-stage distribution system was developed by expanding the previously existing algorithm through consideration of additional transportation environment. Alternative non-linear transportation costs for the same travel distance can be applied for the multi-stage distribution system by estimating the corresponding characteristic values through the collection of the actual data representing the change of transportation circumstances.

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.360-364
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• 2009

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.