• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.399-401
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• 1989

Utilizing an interconnected set of neuron-like elements, the present study is to provide a method of parameter estimation for a second order linear time invariant system of self-tuning controller. The result from the proposed method is evaluated by comparing with those obtained by the recursive least square (RLS) identification algorithm and extended recursive least square (ERLS) algorithm, and it shows that, although the smoothness of system performance is still to be improved, the effectiveness of shorter computing time is demonstrated which may be of considerable value to real time computing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.100-101
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• 2019

본 논문은 유도전동기 고정자 자속 기준 벡터제어에서, 슬립 관계식과 순환 최소자승법을 이용하여 회전자 저항 및 고정자 과도 인덕턴스를 동시에 추정하는 알고리즘을 제안한다. 모의실험을 수행하여, 추정 회전자 저항과 고정자 과도 인덕턴스가 제안된 방법에 의해 각각 실제 값에 수렴함을 보인다.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.1-8
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• 2007

This paper presents a PID automatic gain-tuning algorithm for the electronic throttle valve which is driven by wire. Since the system characteristics of position control for electronic throttle valve are so complicated that both the real time robustness and the manufacturing cost must be considered for mass production. To resolve this paradox, a kind of algorithm called RLS (Recursive Least Square) is adopted for the control of the ETB (Electronic Throttle Body). Using this algorithm, the PID gains can be adjusted automatically with the estimated system parameters. Furthermore, a pre-filter is supplemented for the sake of the robustness against the friction and loads. From the industrial requests for the system, the design specifications are decided as follows: the settling time should be less than 1sec and the overshoot should be kept below 3%. The results of the experiments based on this approach show that the high robustness can be achieved while the system stability is satisfied steadily. A parameter estimation scheme and a gain-tuning algorithm have been properly combined and utilized in this research and the effectiveness is verified through the real experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.303-306
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Journal of Power Electronics
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• v.15 no.2
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• pp.411-418
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• 2015

In this paper, a new method for the online estimation of equivalent series resistances (ESR) of the DC-link capacitors in induction machine (IM) drive systems with a front-end diode rectifier is proposed, where the ESR estimation is conducted during the regenerative operating mode of the induction machine. In the first place, a regulated AC current component is injected into the q-axis current component of the induction machine, which induces the current and voltage ripple components in the DC-link. By processing these AC signals through digital filters, the ESR can be estimated by a recursive least squares (RLS) algorithm. To acquire the AC voltage across the ESR, the DC-link voltage needs to be measured at a double sampling frequency. In addition, the ESR current is simply reconstructed from the stator currents and switching states of the inverter. Experimental results have shown that the estimation error of the ESR is about 1.2%, which is quite acceptable for condition monitoring of the capacitor.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.7
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• pp.1128-1138
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• 2000

This paper presents two different approaches for channel estimation of IMT-2000 pilot symbol-assisted W-CDMA reverse link over Rayleigh fading channels of one and two paths. By obtaining BER performance through computer simulations, the proposed algorithms of 2-point second-order interpolation and IDD BWMA are compared with the performance of existing interpolation and adaptive algorithms. The BER performance of the proposed algorithms is superior to WMSA, linear and second-order Gaussian interpolation, LMS, and RLS algorithm in fast fading channels. In particular, the BER performance of the IDD BWMA algorithm is nearly insensitive for Doppler frequency within simulation range $E_b/N_0$ = 28 dB. The two proposed algorithms also have relatively simple structure and similar processing delay in comparison to the existing algorithms. Therefore, these algorithms are more suitable for high-speed mobile communication environments.

• Journal of Power Electronics
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• v.13 no.6
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• pp.985-990
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• 2013

This paper proposes a novel fault diagnosis scheme using parameter estimation of the stator resistance, especially in the case of the open-phase faults of PMSM drives. The stator resistance of PMSMs can be estimated by the recursive least square (RLS) algorithm in real time. Fault diagnosis is achieved by analyzing the estimated stator resistance of each phase according to the fault condition. The proposed fault diagnosis scheme is implemented without any extra devices. Moreover, the estimated parameter information can be used to improve the control performance. The feasibility of the proposed fault diagnosis scheme is verified by simulation and experimental results.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.97-105
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• 1999

An important task for any software project manager is to be able to predict and control project size. Unfortunately, there is comparatively little work that deals with the problem of building estimation methods for software size in fourth-generation languages systems. In this paper, we propose a new estimation method for estimating for software size based on minimum relative error(MRE) criterion. The characteristic of the proposed method is insensitive to the extreme values of the observed measures which can be obtained early in the development life cycle. In order to verify the performance of the proposed estimation method for software size in terms of both quality of fit and predictive quality, the experiments has been conducted for the dataset I and II, respectively. For the data set I and II, our proposed estimation method was shown to be superior to the traditional method LS and RLS in terms of both the quality of fit and predictive quality when applied to data obtained from actual software development projects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.3
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• pp.1-7
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• 2008

This paper proposes a new QRD-LS adaptive algorithm with computational complexity of O(N). The main idea of proposed algorithm(D-QR-RLS) is based on the fact that the computation for the unit vector of is made from the process during Givens Rotation. The performance of the algorithm is evaluated through computer simulation of FIR system identification problem. As verified by simulation results, this algorithm exhibits a good performance. And, we can see the proposed algorithm converges to optimal coefficient vector theoretically.