• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.62-65
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• 1989

Optimizing transient response for both tracking reference signals and disturbance rejection is determined by the poles and zeros of the transfer function. Thus, optimal pole assignment and how should weighting matrix for the performance index be chosen is very important to achieve optimum transient response. This paper focus its attention on the choosing and analysis of weighting matrix for optimum pole assignment. Optimum pole assignment is defined for linear time-invariant continuous systems.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.407-410
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• 1989

Optimizing transient response for both tracking reference signals and disturbance rejection is determined by the poles and zeros of the transfer function. Thus, optimal pole assignment and how should weighting matrix for the performance index be chosen is very important to achieve optimum transient response. This paper focus its attention on the choosing and analysis of weighting matrix for optimum pole assignment. Optimum pole assignment is defined for linear time-invariant continuous systems.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.193-197
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• 2004

In this paper, a combination problem of controllers which are the same type of $H_{\infty}$ controllers designed with different weighting functions. This approach can remove the difficulty in the selection of the weighting functions. As a sub-controller, the Youla type of $H_{\infty}$ controller is used. In the $H_{\infty}$ controller, Youla parameterization is used to minimize $H_{\infty}$ norm of mixed sensitivity function by using polynomial approach. Computer simulation results show the robustness improvement and the performance improvement.

• Journal of Ocean Engineering and Technology
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• v.27 no.5
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• pp.28-35
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• 2013

In this paper, a research on the composition of the nesting algorithm fitness function is carried out by performing various numerical experiments to inspect how it affects the scrap efficiency, allocation characteristics, and time consumption, targeting the nesting results of ship parts. This paper specifically concentrates on a method to minimize the scrap ratio and efficiently use the well-defined remnants of a raw plate after the nesting process for the remnant nesting. Therefore, experiments for various ship parts are carried out with the weighting factor method, one of the multi-objective optimum design methods. Using various weighting factor sets, the nesting results are evaluated in accordance with the above purposes and compared with each set for each ship part groups. Consequently, it is suggested that the nesting algorithm fitness function should be constructed differently depending on the characteristics of the parts and the needs of the users.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.631-636
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• 2006

In this paper, an algorithm of time series function forecasting using GMDH(group method of data handling) algorithm that gives more weight to the recent data is proposed. Traditional methods of GMDH forecasting gives same weights to the old and recent data, but by the point of view that the recent data is more important than the old data to forecast the future, an algorithm that makes the recent data contribute more to training is proposed for more accurate forecasting. The average error rate of electric power demand forecasting by the traditional GMDH algorithm which does not use data weighting algorithm is 0.9862 %, but as the result of applying the data weighting GMDH algorithm proposed in this paper to electric power forecasting demand the average error rate by the algorithm which uses data weighting algorithm and chooses the best data weighting rate is 0.688 %. Accordingly in forecasting the electric power demand by GMDH the proposed method can acquire the reduced error rate of 30.2 % compared to the traditional method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2081-2086
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• 2005

This paper proposes the receding horizon $H_{\infty}$ predictive control (RHHPC) for systems with a state-delay. We first proposes a new cost function for a finite horizon dynamic game problem. The proposed cost function includes two terminal weighting terns, each of which is parameterized by a positive definite matrix, called a terminal weighting matrix. Secondly, we derive the RHHPC from the solution to the finite dynamic game problem. Thirdly, we propose an LMI condition under which the saddle point value satisfies the well-known nonincreasing monotonicity. Finally, we shows the asymptotic stability and $H_{\infty}$-norm boundedness of the closed-loop system controlled by the proposed RHHPC. Through a numerical example, we show that the proposed RHHC is stabilizing and satisfies the infinite horizon $H_{\infty}$-norm bound.

• Proceedings of the KIEE Conference
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• 2000.07e
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• pp.142-146
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• 2000

In this paper, we are applied the Genetic Algorithm(GA) to design of the robust $H^{\infty}$ speed controller by auto-tuning of the weighting function. GA is used to design of the weighting functions in the robust $H^{\infty}$ controller. To evaluate the performances of the proposed robust $H^{\infty}$ controller, we make an experiment on $H^{\infty}$ speed controller of an actual DC servo- motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Journal of IKEEE
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• v.20 no.2
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• pp.136-142
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• 2016

This paper presents a non-local means (NLM) denoising algorithm based on a new weighting function using a mixed norm. The fidelity of the difference between an anchor patch and the reference patch in the NLM denoising depends on noise level and local activity. This paper introduces a new weighting function based on a mixed norm type of which the order is determined by noise level and local activity of an anchor patch, so that the performance of the NLM denoising can be enhanced. Experimental results demonstrate the objective and subjective capability of the proposed algorithm. In addition, it was verified that the proposed algorithm can be used to improve the performance of the other $l_2$ norm based non-local means denoising algorithms

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1425-1435
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• 2013

The useful method for determining parameters of weighting functions used to design the $H_{\infty}$ current controller for attenuating the current ripple due to saliencies which SPMSM(Surface Permanent Magnet Synchronous Motor) also incorporates is described. To analyze the effect, the current ripple due to the structural and the saturation saliencies, the SPMSM model with nonlinear inductance function depending on the two independent variables, rotor position and stator current is simulated. After analysis, parameters of the weighting functions for $H_{\infty}$ current controller is selected to satisfy the robust stability, robust performance and specific performance in time and frequency domain by using the PSO(Particle Swarm Optimization) algorithm in the linear SPMSM model. Especially, the robust performance is proved that the selected weighting functions play a role in reducing the current ripple caused by the saliencies of SPMSM at the desired frequency range by the simple experiment.