• Proceedings of the KSR Conference
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• 2003.10b
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• pp.510-515
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• 2003

The main objective of this paper is to propose the optimal design method of welded plate girder bridges using genetic algorithm. The objective function considered is the total weight of the welded plate girder. The behavior and design constraints are formulated based on the Korean Railroad Bridge Design Code and DIC Code. Continuous design variables are used to define the cross-sectional dimensions of the member. The GAs (genetic algorithm) is used to solve the nonlinear programming problem. Several examples of minimum weight design are solved to illustrate the applicability of the proposed minimization algorithm. From the results of application examples, the optimum design of welded plate girder is successfully accomplished. Therefore, the proposed algorithm in this paper may be used efficiently and generally for the optimum design of welded plate girders.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1966-1971
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• 2005

Though several previous anti-windup techniques have been proposed, they are limited to linear systems or friction is not considered. Thus this paper proposes a compensation scheme for input-constrained robot systems with friction to cope with the windup phenomenon and shows its effectiveness by simulations. Given a feedback linearizing controller for a robot system designed without considering its input constraint, an additional dynamic compensator is proposed to account for the constraint. The dynamic anti-windup is based on the minimization of a reasonable performance index, and properties of the resulting closed-loop are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.21-25
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• 2004

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine using immune algorithm. The parameter estimation procedure is based on the steady state phase current versus slip and input power versus slip characteristics. The proposed estimation algorithm is of a nonlinear kind based on clonal selection in immune algorithm. The machine parameters are obtained as the solution of a minimization of least-squares cost function by immune algorithm. Simulation shows better results than the conventional approaches.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.90-98
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• 1997

A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilzation of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the systems with constrained inputs and/or states. A neural identifier or a genetic algorithm identifier could be utilized for modeling the partially known systems and the unknown systems. The nature of neural networks as a parallel processor would circumvent the problem of "curwe of dimensionality". The control law has been demonstrated for both a torque input motor and a velocity input motor identified by a genetic algorithm called GENOCOPed GENOCOP.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.4
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• pp.40-45
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• 2002

An AS/RS construction cost minimization model under throughput rate requirement constraint has been developed, whose objective function includes S/R machine cost, storage rack cost, and interrace conveyor cost. S/R machine cost is a function of the storage rack height, the unit load weight, and the control logic used by the system, while storage rack cost is a function of the storage rack height, the weight and the volume of the unit load. Since the model is a nonlinear integer programming problem which is very hard to solve exactly with large problem size, a solution procedure is developed to determine the height and the length of the storage rack with a fixed number of S/R machines, while increasing the number of S/R machines one by one to meet the throughput rate requirement.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1999.11a
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• pp.279-284
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• 1999

Although the switched reluctance motor (SRM) has a several advantages such as simple magnetic structure, robustness, wide range of speed characteristics and simple driving, it has a considerable inherent torque ripple and speed variation duet to the driving characteristics of pulse current waveform and the nonlinear inductance profile. The high torque ripple and speed variation inhibits wide application. The minimization of the torque ripple is very important in high performance servo drive applications, which require smooth operation with minimum torque pulsations. This paper presents the new SRM torque modeling technique for the control of instantaneous torque. The SRM is modeled by the database of torque profiles for every small variation in currents and rotor angles, which is inferred from the several measured data by the adaptive neuro-fuzzy inference technique. Simulation results demonstrating the effectiveness of proposed torque modeling technique are presented.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.183-193
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• 2000

In this paper we use measure theory to solve a wide range of second-order boundary value ordinary differential equations. First, we transform the problem to a first order system of ordinary differential equations(ODE's)and then define an optimization problem related to it. The new problem in modified into one consisting of the minimization of a linear functional over a set of Radon measures; the optimal measure is then approximated by a finite combination of atomic measures and the problem converted approximatly to a finite-dimensional linear programming problem. The solution to this problem is used to construct the approximate solution of the original problem. Finally we get the error functional E(we define in this paper) for the approximate solution of the ODE's problem.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.53-68
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• 2009

In this paper, we address a problem for minimizing the number of items inspected in a back-light-unit (BLU) inspection system, which includes a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective, we make a steady-state flow analysis between nodes (or shops), and derive the steady-state amount of flows between nodes and defective rates by solving a nonlinear balance equation. We provide an enumeration method for determining an optimal value of K which minimizes the number of items inspected. Our methodology could be applied and extended to similar situations with slight modification.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.64-70
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• 1994

Predictive neural network models are powerful speech recognition models based on a nonlinear pattern prediction. But those models suffer from poor discrimination between acoustically similar words. In this paper we propose an discriminative training algorithm for predictive neural network models. This algorithm is derived from GPD (Generalized Probabilistic Descent) algorithm coupled with MCEF(Minimum Classification Error Formulation). It allows direct minimization of a recognition error rate. Evaluation of our training algoritym on ten Korean digits shows its effectiveness by 30% reduction of recognition error.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.119-135
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• 2010

In this paper, we readdress the optimization problem for minimizing the inspection cost in a back-light unit inspection system, which forms a network including a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective function when the system is in a steady state, assuming that the number of nonconforming items in a lot follows a binomial distribution when a lot is formed for inspection, we make a steady-state network flow analysis between shops, and derive the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration method for determining an optimal value of K which minimizes our objective function. In addition, we compare our results numerically with previous ones.