• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.100-107
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• 2003

This paper represents a disturbance compensation control for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feed forward compensator design based on adaptive estimation by Filtered-x least mean square (FXLMS) algorithm is proposed. The convergence properties of the FXLMS algorithm are discussed and its conditions for the asymptotic convergence are derived theoretically. The effectiveness of the proposed method and the theoretical proof are verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.164-167
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• 1996

This paper presents an off-line P.I.D parameter estimation method during normal operation in power plant. The process parameters are estimated using the recursive least square method. The controller parameters are estimated on the basis of desired characteristics of the dynamic model of the closed-loop control.

• 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 IEEK Conference
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• 2000.06e
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• pp.124-126
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• 2000

The Minimum-Norm Least-Square(MNLS) approach based on lead field theory is an useful method to find an unique inverse solution for the measured magnetic field. The lead field depends on head geometry and location of sources and sensors. So, optimization of sensor array location is important issue for MNLS estimation. In this paper, we present an investigation for the optimization of sensor array location in computer simulation.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.130-136
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• 2009

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of Li-ion battery indicates highly dependant of temperatures. The system pole and internal resistance changes 6.6 and 18 times at $-20^{\circ}C$, comparing with those at $25^{\circ}C$, respectively. These results will be utilized on constructing model-based state observer or an on-line identification and an adaptation of the model parameters in battery management systems for hybrid electric vehicle applications.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.259-265
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• 2017

Magnetometer calibration must be performed before the use of three-axis magnetometers to ensure the accuracy of orientation estimation. Recently, one of the most popular calibration approaches is the ellipsoid fitting technique due to its high performance in calibration. To date, in fact, performances of the existing ellipsoid fitting methods have been evaluated with full range rotation data. However, in case of the calibration of magnetometers attached to vehicles, ships, and planes, it is very difficult to collect the full range rotation data since their allowable ranges in terms of roll and pitch are limited to small. This constraint may result in serious performance degradation of some ellipsoid fitting algorithms. Therefore, to be practical, this paper proposes a weighted least square-based magnetometer calibration method that is robust in roll-pitch limited conditions. Furthermore, the proposed method is a linear approach and thus is free from the well-known initial value issue in nonlinear approaches. Experimental results show the superiority of the proposed method to other ellipsoid-fitting calibration methods.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.137-144
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• 2005

An estimation technique of the joint diameter distribution using the least square method is suggested. When utilizing the technique by Song and Lee, the diameter distribution would be obtained only from the trace length distribution defined in an infinite window after the trace length distribution is estimated from the contained trace length distribution. With the new technique, however, the diameter distribution can be directly obtained from the sample histogram of the contained trace lengths. Compared with the previous technique, it shows a more accurate result for small sizes of joint samples and provides the joint geometry parameter of volumetric frequency. Verification of this new technique was completed by using Monte Carlo simulations.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.527-539
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• 2023

In the positioning algorithm of two-dimensional planar sensor array, the estimation error of time difference-ofarrival (TDOA) algorithm is difficult to avoid. Thus, how to achieve accurate positioning is a key problem of the positioning technology based on planar array. In this paper, a method of sensor reliability discrimination is proposed, which is the foundation for selecting positioning sensors with small error and excellent performance, simplifying algorithm, and improving positioning accuracy. Then, a positioning model is established. The estimation characteristics of the least square method are fully utilized to calculate and fuse the positioning results, and the non-uniform weighting method is used to correct the weighting factors. It effectively handles the decreased positioning accuracy due to measurement errors, and ensures that the algorithm performance is improved significantly. Finally, the characteristics of the improved algorithm are compared with those of other algorithms. The experiment data demonstrate that the algorithm is better than the standard least square method and can improve the positioning accuracy effectively, which is suitable for vibration detection with large noise interference.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.