• International Journal of Quality Innovation
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• v.4 no.1
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• pp.191-204
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• 2003

The target costing technique, mathematically discussed by Sauers, only uses the $C_p index along with Taguchi loss function and $\bar{X}$-P control charts to setup goal control limits. The new specification limits derived from Taguchi loss function is linked through the $C_p value to $\bar{X}$-P control charts to obtain goal control limits. Studies have shown that the point estimator of the $C_p index, $C_p, could vary from time to time due to the sampling error. The suggested approach is to use confidence intervals, especially the lower confidence intervals, to replace the point estimator. Therefore, an improvement on target costing technique is presented by applying the lower confidence interval of the $C_p index and using both Taguchi and Spiring's loss functions together with $\bar{X}$-P charts to make this technique more robust in practice. An example is also provided to illustrate how the improved target costing technique works.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.35-42
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• 2004

The control systems with friction cause the steady state error and slow response, because friction is a sensitive to the change of system condition and has highly nonlinear characteristics. To overcome these problems and do precise position control for a ball-screw system, we use Coulomb friction estimator and the sliding mode control(SMC) to compensate its negative effect. The applied SMC for tracking position has a characteristics of robust stability and reducing chattering, and is derived from the Lyapunov stability theorem and reaching condition. Compensating the estimated friction torque to the bounded disturbance term of the SMC's equivalent control input, it has a tracking performance better than the PID from the experimental results.

• Communications for Statistical Applications and Methods
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• v.21 no.3
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• pp.261-274
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• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.576-578
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• 1994

In this. paper, a new technique to estimate both the instantaneous speed and disturbance load torque using a low precision shaft encoder in very low speed range is proposed. To detect the instantaneous speed and disturbance load torque, the Kalman filter which is an optimal full order estimator is used. Experimental results conform the validity of the proposed estimation technique. The effects of parameter variations are discussed, and it is verified that the system is robust to the modeling error.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1854-1855
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• 2006

In this paper, the Takagi-Sugeno (TS) fuzzy state estimation scheme, which is suggested for a steady state estimator using standard Kalman filter theory with uncertainties. In that case, the steady state with uncertain can be represented by the TS fuzzy model structure, which is further rearranged to give a set of uncertain linear model using standard Kalman filter theory. And then the unknown uncertainty is regarded as an additive process noise. To optimize fuzzy system, we utilize the genetic algorithm. The steady state solutions can be found for proposed linear model then the linear combination is used to derive a global model. The proposed state estimator is demonstrated on a truck-trailer.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.94-100
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• 2002

The conventional sliding mode control (SMC) technique requires a priori knowledge of the upperbounds of disturbances and/or modeling uncertainties to assure robustness. This, however, may not be easy to obtain in practical situation. This paper presents a new methodology, a sliding mode control with disturbance estimator (SMCDE), which offers a robust control performance without a priori knowledge about the disturbance. The proposed technique is featured by an average value of the imposed disturbance over a certain period. A nonlinear spring-mass-damper system and a two-link robot system are adopted as illustrative application examples. Control performances such as estimation error and tracking error are compared between the proposed methodology and conventional scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.842-848
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• 2014

In this paper, an improved method RMBE (Resizable Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. At the target engaging scenario, the IIR target measurement is separated by various parts. In this case, target object changing is important to accurate target intercept. Therefore, we need robust target size estimator. Our proposed method resize estimated target size with MC-1 (Markov Chain I) for accurate target size estimation. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed RMBE has improved performance than MBE.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.880-888
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• 2006

This paper presents the sliding mode control with the perturbation estimator for a nonlinear control system in the presence of perturbations including external disturbances, unpredictable parameter variations, ana unstructured dynamics. The proposed perturbation estimator is based on the Recursive Linear Smoothed Newton predictive algorithm so that it is effective to attenuate an undesired noise in high frequency band and to predict the present perturbation signal from the previous ones. Compared to conventional sliding mode control (SMC) and sliding mode control with perturbation estimation (SMCPE) introduced by Elmali and Olgac, the control algorithm proposed in this study can offer better tracking control performances and more feasible estimation characteristics. The effectiveness and superiority of the proposed control strategy are demonstrated by a series of simulations on the position tracking control of a simple two-link robot manipulator subject to velocity feedback signals including white noises.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.609-615
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• 2007

We propose an optimized adaptive PID control scheme. This paper is focused on the development of model reduction as well as a new adoptive control structure (viz. a recursive least square estimation (RLSE) method-based structure) that is constructed with smith-predictor structure and a real time estimator. The estimator adjust parameters of a reduced model in real time. It leads to robust and superb control performance for the noise or variation of parameters of process. Experimental study reveals that the proposed control structure exhibits more superb output performance in comparison to some previous methods.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.165-171
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• 2002

The conventional sliding mode control(SMC) technique requires a priori knowledge of the upperbounds of disturbances or/and modeling uncertainties to assure robustness. This, however, may not to be easy to obtain in practical situation. This paper presents a new methodology, sliding mode control with disturbance estimator(SMCDE), which offers a robust control performance without a priori knowledge about the disturbance. The proposed technique is featured by an average value of the imposed disturbance over a certain period. A nonlinear spring-mass-damper system is adopted as an illustrative example, and a comparative work between the conventional technique and the present one is undertaken.