• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.324-329
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• 2002

In this paper, the guaranteed cost filtering design method for linear time delay systems with convex bounded uncertainties in discrete-time case is presented. The uncertain parameters are assumed to be unknown but belonging to known convex compact set of polytotype less conservative than norm bounded parameter uncertainty. The main purpose is to design a stable filter which minimizes the guaranteed cost. The sufficient condition for the existence of filter, the guaranteed cost filter design method, and the upper bound of the guaranteed cost are proposed. Since the proposed sufficient conditions are LMI(linear matrix inequality) forms in terms of all finding variables, all solutions can be obtained simultaneously by means of powerful convex programming tools with global convergence assured. Finally, a numerical example is given to check the validity of the proposed method.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.808-813
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• 1999

A fuzzy learning method to control an unstable and multivariable system is presented in this paper, Because the multivariable system has generally a coupling effect between the inputs and outputs, it is difficult to find its modeling equation or parameters. If the system is unstable, initial condition rules are needed to make it stable because learning is nearly impossible. Therefore, this learning method uses the initial rules and introduces a cost function composed of the actual error and error-rate of each output without the modeling equation. To minimize the cost function, we experimentally got the Jacobian matrix in the operating point of the system. From the Jacobian matrix, we can find the direction of the convergence in the learning, and the optimal control rules are finally acquired when the fuzzy rules are updated by changing the portion of the errors and error rates.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.475-478
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• 1998

The matrix hypercube MH(2,n) is the interconnection network which improves the network cost of the hypercube. In this paper, we propose an algorithm for one-to-all broadcasting in the matrix hypercube MH(2,n). The algorithm can broadcast a message to 22n nodes in O(n) time. The algorithm uses the rich structure of the matrix hypercubes and works by recursively partitioning the original matrix hypercubes into smaller matrix hypercubes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.929-935
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• 2011

Customers hardly change to electric prices in old days because electricity is essential commodity, while demand changes with price after deregulation. It's explained by price-based demand response with demand-elasticity matrix. Also all of the customers have had identical demand-price elasticity matrix till now. But in a practical power system, various customers are present with taking a variety of demand-price elasticity. Therefore this paper proposes demand-price sensitivity to represent different demand-price elasticity. Also as proposing demand-reliability sensitivity, it is modeling various customers' characteristics to reliability. And then this paper calculates total expected interruption cost of customer from the customer interruption cost and the demand-reliability sensitivity. A total expected interruption cost of system is shown as opportunity cost of a generation cost.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.151-157
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• 2008

A non-fragile guaranteed cost control (GCC) problem is presented for a class of discrete time-delay nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The systems are assumed to have norm-bounded time-varying uncertainties in the matrices of state, delayed state and control gains. Sufficient conditions are first obtained which guarantee that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound. Then the design method of the non-fragile guaranteed cost controller is formulated in terms of the linear matrix inequality (LMI) approach. A numerical example is given to illustrate the effectiveness of the proposed design method.

• KIEAE Journal
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• v.16 no.1
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• pp.47-55
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• 2016

Purpose: Long-life housing causes unavoidable cost increase while providing higher durability, flexibility, and repair easiness compare to those of normal apartment. The effectiveness should be evaluated considering the level of passing mandatory Long-life housing Certification System when supplying specific size of apartment complex. Thus, it is essential to identify the estimated costs and the obtainable grade by applying the optional element technologies selectively during the design phase. This study aimed to suggest the technology influence matrix(TIM) to support decision-making of element technologies in planning stage of long-life housing. Method: The technology influence matrix was established based on the property information about applicable element technologies for long-life housing such as construction methods, interface types, cost data, and certification-related characteristics. The usefulness of TIM was verified through case study, in which TIM was applied to the exclusive housing unit and the influences from four areas of quantity, cost, certification, and schedule were identified and calculated. Result: TIMs covering four areas representing the essential planning factors were developed, and are expected to contribute to sound decision-making in planning long-life housing.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.194-200
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• 2009

This study provides a heuristic algorithm to solve the locating problem of repair service centers (RSCs). To enhance the customer service level with more satisfaction and quicker responsiveness, the locating problem of RSCs has become one of the important issues in reverse supply chain management. This problem is formulated as a zero-one mixed integer programming in which an exiting distributor will be considered to be an un-capacitated repair service center for the objective of cost-minimizing. Since logistical costs are highly interrelated with the multinational location of distributors and RSCs, the fixed cost for setting a repair service center, variable cost, transportation cost, and exchange rates are considered in this study. Recognizing the selection of un-capacitated RSCs' locations is a combinatorial optimization problem and is a zero-one mixed integer programming with NP-hard complexity, we provide a heuristic algorithm named as incremental cost matrix procedure (ICMP) to simplify the solving procedure. By using the concise and structural cost matrix, ICMP can efficiently screen the potential location with cost advantage and effectively decide which distributor should be a RSC. Results obtained from the numerical experiments conducted in small scale problem have shown the fact that ICMP is an effective and efficient heuristic algorithm for solving the RSCs locating problem. In the future, using the extended ICMP to solve problems with larger industrial scale or problems with congestion effects caused by the variation of customer demand and the restriction of the RSC capacity is worth a further investigation.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.348-351
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• 1995

This note proposes a robust LQR method for systems with structured real parameter uncertainty based on Riccati equation approach. Emphasis is on the reduction of design conservatism in the sense of quadratic performance by utilizing the uncertainty structure. The class of uncertainty treated includes all the form of additive real parameter uncertainty, which has the multiple rank structure. To handle the structure of uncertainty, the scaling matrix with block diagonal structure is introduced. By changing the scaling matrix, all the possible set of uncertainty structures can be represented. Modified algebraic Riccati equation (MARE) is newly proposed to obtain a robust feedback control law, which makes the quadratic cost finite for an arbitrary scaling matrix. The remaining design freedom, that is, the scaling matrix is used for minimizing the upper bound of the quadratic cost for all possible set of uncertainties within the given bounds. A design example is shown to demonstrate the simplicity and the effectiveness of proposed method.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.