• Journal of Power Electronics
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• v.17 no.1
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• pp.149-160
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• 2017

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed estimation method based on a strong tracking extended Kalman filter with a least-square algorithm (LS-STEKF) for induction motors is proposed in this paper. With this method, a fading factor is introduced into the covariance matrix of the predicted state, which forces the innovation sequence orthogonal to each other and tunes the gain matrix online. In addition, the estimation error is adjusted adaptively and the mutational state is tracked fast. Simultaneously, the fading factor can be continuously self-tuned with the least-square algorithm according to the innovation sequence. The application of the least-square algorithm guarantees that the information in the innovation sequence is extracted as much as possible and as quickly as possible. Therefore, the proposed method improves the model adaptability in terms of actual systems and environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by experimental results.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.97-105
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• 2007

We consider a nonparametric additive risk model that is based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huller and Mckeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1829-1830
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• 2008

The paper deals with leader-follower formations of nonholonomic mobile robots using least square method in order to maintain the formation constantly. The nonholonomic property of the mobile robot cause us to use the least square method. Then, the performance of the developed formation controller is verified by simulation results.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.643-654
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• 2000

In this paper, we review some class of t-norms on which fuzzy arithmetic operations preserve the shapes of fuzzy numbers and the Hausdorff-distance between fuzzy numbers as the measure of distance between fuzzy numbers. And we suggest the least Hausdorff-distance square method for fuzzy linear regression model using shape preserving fuzzy arithmetic operations.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.49-50
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• 2006

We consider a nonparametric additive risk model that are based on splines. This model consists of both purely and smoothly nonparametric components. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.208-210
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• 1998

A high speed digital distance relaying algorithm based on a modified least square error method is proposed. To obtain stable phasor values very Quickly, first, a lowpass filter which has very short transient period and no overshoot is used. Secondly, the conventional least square error method is modified to the one having the data window of 3 samples by applying a FIR filter which removes the DC-offset component in current relaying signals.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.843-849
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• 1996

The least square estimation is used frequently in experimental modal analysis techinque to eliminate noise signals. However, identified modal parameters are sometimes inaccurate, since the least squre estimation is sensitive to noise. In this paper, a new total least squre estimation, which is robust to noise signals, is developed and applied to experimental modal analysis technique such as Prony method and Circle Fit method. Several simulated results show that the proposed method is robuster to noise than conventional method.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.565-567
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• 2008

In the present study, a least square/level set based two-phase flow code has been developed using finite element discretization, which can be utilized for the analysis of a free surface flow problem in a complex geometry. Since the finite element method is employed for the spatial discretization of governing equations, an unstructured mesh can be naturally adopted for the level set simulation of a bubble-in-liquid flow without an additional load for the code development except that solution methods of the hyperbolic type redistancing and advection equations of the level set function should be devised in order to give a bounded solution on the unstructured mesh. For the discretization of hyperbolic type redistancing and advection equations, least square method is adopted. From the numerical experiments of the present study, it is shown that the proposed method is both robust and accurate.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.7
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• pp.855-862
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• 1999

A high speed digital distance relaying algorithm based on a least square error method is proposed. To obtain stable phasor values very quickly, first, a lowpass filter which has very short transient period and no overshoot is presented. Secondly, the least square error method having the data window of 3 samples is used by applying a FIR filter which removes the DC-offset component in current relaying signals. Test results show that the proposed distance relaying algorithm detects most of internal faults within a half cycle after faults in a 154[kV] overhead transmission line system.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.217-224
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• 2012

Location-Based Services(LBS) is a service that provide location information by using communication network or satellite signal. In order to provide LBS precisely and efficiently, we studied how we can reduce the error on location determination of objects such people and things. We focus on using the least square method and triangulation positioning method to improves the accuracy of the existing location determination method. Above two methods is useful if the distance between the AP and the tags can be find. Though there are a variety of ways to find the distance between the AP and tags, least squares and triangulation positioning method are wildely used. In this thesis, positioning method is composed of preprocessing and calculation of location coordinate and detail of methodology in each stage is explained. The distance between tag and AP is adjusted in the preprocessing stage then we utilize least square method and triangulation positioning method to calculate tag coordinate. In order to confirm the performance of suggested method, we developed the test program for location determination with Labview2010. According to test result, triangulation positioning method showed up loss error than least square method by 38% and also error reduction was obtained through adjustment process and filtering process. It is necessary to study how to reduce error by using additional filtering method and sensor addition in the future and also how to improve the accuracy of location determination at the boundary location between indoor and outdoor and mobile tag.