• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.817-826
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• 1987

An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

• Earthquakes and Structures
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• v.22 no.2
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• pp.157-168
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• 2022

A moment-independent importance measure analysis approach was introduced to quantify the effects of structural uncertainty parameters on probabilistic seismic demands of simply supported girder bridges. Based on the probability distributions of main uncertainty parameters in bridges, conditional and unconditional bridge samples were constructed with Monte-Carlo sampling and analyzed in the OpenSees platform with a series of real seismic ground motion records. Conditional and unconditional probability density functions were developed using kernel density estimation with the results of nonlinear time history analysis of the bridge samples. Moment-independent importance measures of these uncertainty parameters were derived by numerical integrations with the conditional and unconditional probability density functions, and the uncertainty parameters were ranked in descending order of their importance. Different from Tornado diagram approach, the impacts of uncertainty parameters on the whole probability distributions of bridge seismic demands and the interactions of uncertainty parameters were considered simultaneously in the importance measure analysis approach. Results show that the interaction of uncertainty parameters had significant impacts on the seismic demand of components, and in some cases, it changed the most significant parameters for piers, bearings and abutments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.163-171
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• 2012

The signal model and weighted-average based estimation techniques are proposed to estimate the angle-of-arrival (AOA) parameters of multiple clusters for a low data rate ultrawide band (LR-UWB) based wireless positioning system. It is observed that the weighted-average based AOA estimation technique gives an optimal AOA estimate under few clusters condition, and the average based AOA estimation technique gives a correct AOA estimate under many clusters condition through computer simulation. Also, we can observe that the variance estimation error decreases as SNR increases, and the proposed techniques are superior to the conventional technique from the viewpoint of performance.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.713-723
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• 2013

An objective Bayesian estimation procedure of the two-parameter Pareto distribution is presented under the reference prior and the noninformative prior. Bayesian estimators are obtained by Gibbs sampling. The steps to generate parameters in the Gibbs sampler are from the shape parameter of the gamma distribution and then the scale parameter by the adaptive rejection sampling algorism. A numerical study shows that the proposed objective Bayesian estimation outperforms other estimations in simulated bias and mean squared error.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.347-353
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• 2019

Electric-hydraulic sever cylinders are used in many offshore applications such as wind energy farms, solar farms and plants. Jack-up barges are often used for these offshore system operations. Jack-up barge control is up/down by hydraulic cylinder position control. Working in harsh environments can lead to changes in internal parameters. This nonlinearity makes precise control difficult. In order to overcome the problems, we proposed a method of unknown-parameter estimation algorithm based on measurements obtained by system. In this paper, we employee Unscented Kalman filter (UKF) to estimate states and unknown-parameter from augmented nonlinear equation. Performance of estimation results is verified in simulation on an environments of Matlab. The estimation results of the state and unknown-parameter show that the estimation error of unknown-parameter is reduced according to decreasing the state estimation error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4873-4888
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• 2018

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.254-261
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• 2003

In mold and die shops, NC machining process mainly affects the quality of the machined surface and the manufacturing time of molds and dies. The estimation of NC machining time is a prerequisite to measure the machining productivity and to generate a process schedule, which generally includes the process sequence and the completion time of each process. It is required to take into account dynamic characteristics in the estimation, such as the ac/deceleration of NC machine controllers. Intensive observations at start and end points of NC blocks show that a minimum feedrate, a key variable in a machining time model, has a close relation to a block distance, an angle between blocks, and a command feedrate. Thus, this study addresses regression models for the minimum feedrate estimation on short and long NC blocks considering these parameters. Furthermore, machining time estimation models by the four types of feedrate behaviors are suggested based on the estimated minimum feedrate. To show the validity of the proposed machining time model, the study compares the estimated with the actual machining time in the sculptured surface machining of several mold dies.

• Journal of Sensor Science and Technology
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• v.26 no.6
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• pp.371-378
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• 2017

An accurate and robust estimation of center of rotation (CoR) using optical marker trajectory is crucial in human biomechanics. In this regard, the performances of the two prevailing least-squares methods, the Gamage and Lasenby (GL) method, and the Chang and Pollard (CP) method, are verified in this paper. While both methods are sphere-fitting approaches in closed form and require no tuning parameters, they have not been thoroughly verified by comparison of their estimation accuracies. Furthermore, while for both methods, results for stationary CoR locations are presented, cases for perturbed CoR locations have not been investigated for any of them. In this paper, the estimation performances of the GL method and CP method are investigated by varying the range of motion (RoM) and noise amount, for both stationary and perturbed CoR locations. The difference in the estimation performance according to the variation in the amount of noise and RoM was clearly shown for both methods. However, the CP method outperformed the GL method, as seen in results from both the simulated and the experimental data. Particularly, when the RoM is small, the GL method failed to estimate the appropriate CoR while the CP method reasonably maintained the accuracy. In addition, the CP method showed a considerably better predictability in CoR estimation for the perturbed CoR location data than the GL method. Accordingly, it may be concluded that the CP method is more suitable than the GL method for CoR estimation when RoM is limited and CoR location is perturbed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.328-331
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• 2011

준정적 횡하중을 재하 받는 철근콘크리트 보-기둥 접합부의 전단강도에 대한 주요 영향요인을 Bayesian parameter estimation의 신뢰성 이론 접목을 통해 검토하였다. 이와 같은 연구 scope의 수행을 위해 철근콘크리트 보-기둥의 실험 database가 구축되었다. 실험 database는 일정한 criteria을 적용하여 구축되었으며, 포함된 시편들은 최종적으로 접합부 내의 전단파괴가 지배하는 경우들이다. 포함된 시편들의 상세는 ACI (American Concrete Institute) 352R-02를 기준으로 평가되어졌다. 보-기둥 접합부의 전단강도에 영향 요인을 편중되지 않게 평가하고자, Bayesian parameter estimation의 신뢰성 이론을 적용하였다. Bayesian parameter estimation의 적용을 통해 전단강도에 영향이 적은 변수 (not informative parameter)를 순차적으로 제거 (stepwise removal process)함으로 주요 영향요인의 우선 순위를 확인할 수 있었다. 검토된 8개의 변수들 중에서, 횡하중을 재하 받는 철근콘크리트 보-기둥의 전단강도는 주로 콘크리트 압축강도, in-plane geometry, 종방향 보의 주철근 그리고 접합부 내의 구속철근 순으로 영향을 줌을 알 수 있었다.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.