• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.572-577
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• 1992

In this paper, the optimal homing guidance problem is investigated for the general missile/target models described in the state-space. The closed-form solution of the optimal guidance law derived, and its asymptotic properties are studied as the time-to-go goes to infinity or zero. Futhermore, several approximate solutions of the optimal guidance law are suggested for real-time applications.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.5
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• pp.360-366
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• 1987

The design problem of optimal constant PIDM (proportional-integral-derivative and measurable variable) feedback controller for linear time-invariannt systems is investigated with the time-weighted quadratic performance index. Necessary conditions for an optimality of the controller are derived and an algorithm for computing the optimal feedback gain is presented. It is shown via example that the design mithod using the time-weighted quadratic performance index improves the transient responses of the closed-loop system.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.2
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• pp.3-17
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• 1994

This paper presents an EMQ model which determines an optimal manufacturing lot size in an unreliable machine. The machine has an exponentially distributed life time, and requires a constant time to repair when it fails. We 1) derive an average cost function, 2) obtain an optimal lot size and show that it is unique, 3) carry out sensitivity analysis to examine the effect of machine parameters (life time, time to repair) to optimal lot size.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1455-1458
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• 1996

In this paper trajectory tracking control problems are described for a robot manipulator by using pneumatic actuator. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with input time-delay by the step response. Then, an optimal servo controller is designed by taking account of such a time-delay. The effectiveness of the proposed control method is illustrated through some simulations and experiments for the robot manipulator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.372-377
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• 1996

A time-optimal control law for quick, strongly nonlinear systems like revolute robots has been developed and demonstrated. This procedure involves the utilization 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 known and unknown systems with constrained inputs and/or states. The nature of neural networks as a parallel processor would circumvent the problem of "curse of dimensionality".ity".uot;.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.293-303
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• 2006

This paper describes a numerical scheme for optimal control of a time-dependent linear system to a moving final state. Discretization of the corresponding differential equations gives rise to a linear algebraic system. Defining some binary variables, we approximate the original problem by a mixed integer linear programming (MILP) problem. Numerical examples show that the resulting method is highly efficient.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.1
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• pp.30-37
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• 2001

The purpose of this study is to present the method to determine the optimal stop time of HVAC using Artificial Neural Network model, one of the learning methods. For this, the performance of determining the stop time of HVAC for unexperienced learning data was evaluated, and time interval for measurement of input data and permissible error needed for practical application of ANN model were presented using the results of daily simulation.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.1
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• pp.22-30
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• 2005

The purpose of this study is to present a method to determine the optimal stop time of HVAC using the Artificial Neural Network model, which is one of the learning methods. For this, the performance of determining the stop time of HVAC for unexperienced learning data was evaluated, and time interval for measurement of input data and permissible error needed for practical application of ANN model were presented using the results from daily simulation.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.263-266
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• 1996

A method to determine an optimal temperature trajectory that guarantees polymer products having controlled molecular weight distribution and desired values of molecular weight is presented. The coordinate transformation method and the optimal control theory are applied to a batch PMMA polymerization system to calculate the optimal temperature trajectory. Coordinate transformation method converts the original fixed-end-point, free-end-time problem to a free-end-point, fixed-end-time problem. The idea is that by making the reactor temperature track the optimal temperature trajectory one may be able to produce polymer products having the prespecified physical property in a minimum time. The on-line control experiments with the PID control algorithm have been conducted to establish the validity of the scheme proposed in this study. The experimental results show that prespecified polymer product could be obtained with tracking the calculated optimal temperature trajectory.