• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.363-369
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• 1999

In this paper, we design the robust $H_{\infty}$ controller for water level control of steam generator using a mixed $H_{\infty}$ optimization with model-matching method. Firstly we choose the desired model which has good disturbance rejection performance. Secondly we design a stabilizing controller to keep the model-matching error small and also provide sufficiently large stability margin against additive perturbations of the nominal plant. Simulation results show that proposed robust $H_{\infty}$ controller at specific power operation has satisfactory performances against the variations of load power, steam flow rate, primary circuit coolant temperature, and feedwater temperature. It can be also observed that the proposed robust $H_{\infty}$ controller exhibits better robust stability than conventional PI controller.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.110-113
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• 1991

An electromagnet is one of the important devices in magnetic levitation system. Its weight takes large part in the total weight of a vehicle. That is the reason why it is important to design the electromagnet optimally to maximize the attraction force with constant volume. This study presents the optimum value of the design variables which can produce the maximal attraction force under constant magnet volume. For this, non-linear programming in optimization technique is used. And to confirm reliability of the results, the optimally designed electromagnet is analyzed by FEM. The attraction force of the optimally designed electromagnet is increased maximally 72% compared with that of the basic model. And the results obtained by non-linear programming has 30% error compared with that of FEM.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.31.1-31.1
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• 2011

In this study, we investigated alignment state estimation performances of the three methods i.e. merit function regression (MFR), differential wavefront sampling (DWS) and Multiple Design Configuration Optimization (MDCO). The three target optical systems are 1) a two-mirror Cassegrain system for deep space Earth observation, 2) intermediate size three-mirror anastigmat for Earth ocean monitoring, and 3) extremely large segmented optical system for astronomical observation. We ran alignment state estimation simulation for several alignment perturbation cases including 1mm to 10mm in decenter and from 0.1 to 1 degree in tilt perturbation error for the two-mirror Cassegrain system. In general, we note that MDCO shows more competitive estimation performance than MFR and DWS. The computational concept, case definition and the simulation results are discussed with implications to future works.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.294-297
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• 2004

Mean squared error (MSE) is an effective criterion to combine the mean and the standard deviation responses in dual response surface optimization. The bias and variance components of MSE need to be weighted properly in the given problem situation. This paper proposes a systematic method to determine the relative weights of bias and variance in accordance with a decision maker's prior and posterior preference structure.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.50-56
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• 2000

This paper presents the design of an optimal state feedback controller for container cranes under some design specifications. To do this, the nonlinear equation of a container crane system is linearized and then augmented to eliminate the steady-state error, and some constraints are derived from the design specifications. Designing the controller involves a constrained optimization problem which classical gradient-based methods have difficulties in handling. Therefore, a real-coding genetic algorithm incorporating the penalty strategy is used. The responses of the proposed control system are compared with those of the unconstrained optimal control system to illustrate the efficiency.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.427-449
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• 2014

A hybrid optimization method for the identification of state-space models is presented in this study. Hybridization is succeeded by combining the advantages of deterministic and stochastic algorithms in a superior scheme that promises faster convergence rate and reliability in the search for the global optimum. The proposed hybrid algorithm is developed by replacing the original stochastic mutation operator of Evolution Strategies (ES) by the Levenberg-Marquardt (LM) quasi-Newton algorithm. This substitution results in a scheme where the entire population cloud is involved in the search for the global optimum, while single individuals are involved in the local search, undertaken by the LM method. The novel hybrid identification framework is assessed through the Monte Carlo analysis of a simulated system and an experimental case study on a shear frame structure. Comparisons to subspace identification, as well as to conventional, self-adaptive ES provide significant indication of superior performance.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.78-83
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• 1999

This paper concerns a least square method for pattern optimization of a thinned sensor array in which the squared error between a desired pattern and a synthesized one is minimized. A weighting function is applied in the function with respect to the array visual range for a symmetric and asymmetric configuration for sensor spacing. An exponential weighting function is proposed to control the sidelobes efficiently around the mainbeam and to generate a uniform sidelobe. The resulting pattern may be employed to eliminate incoming interferences distributed uniformly around the array visual range.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.282-289
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• 2009

This paper presents an estimation technique of the equivalent circuit parameters for an underwater acoustic piezoelectric transducer from the measured impedance. Estimated equivalent circuit can be used for the design of the impedance matching network of the sonar transmitter. A fitness function is proposed to minimize the error between the calculated impedance of the equivalent circuit and the measured impedance of the transducer. The equivalent circuit parameters are estimated by using the fitness function and the PSO(Particle Swarm Optimization) algorithm. The effectiveness of the proposed method is verified by the applications to a sandwich-type transducer and a dummy load. In addition, the impedance matching network is also designed by using the estimated equivalent circuit model.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.357-362
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• 2002

The underlying principle of fault detection via unknown input observer is to make the state estimation error independent of disturbances(or unknown inputs). In this paper, we present a systematic method that can exactly assign the eigenstructure with disturbance suppression and fault isolation capability. A desired eigenstructure for both fault isolation and disturbance suppression is obtained by an optimization method. For the dual purposes, terms for fault isolation and far disturbance suppression are included in the employed objective function for the optimization. The proposed scheme is applied to a simple example to confirm the usefulness of the method.