• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Journal of the Korean Society for Precision Engineering
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• 제31권10호
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• pp.947-954
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• 2014

Performance of next generation susceptor is affected by temperature uniformity in order to produce reliably large-sized flat panel display. In this paper, we propose a learning estimation model of susceptor to predict and appropriately assess the temperature uniformity. Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) are compared for the suitability of the learning estimation model. It is proved that SVMs provides more suitable verification of uniformity modeling than ANNs during each stage of temperature variations. Practical procedure for uniformity estimation of susceptor temperature was developed using the SVMs prediction algorithm.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.529-538
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• 2006

Separating a reentry vehicle into warhead and body is a conventional and efficient means of producing a huge decoy and increasing the kinetic energy of the warhead. This procedure causes the radar to track the body, whose radar cross section is larger, and ignore the warhead, which is the most important part of the reentry vehicle. However, the procedure is difficult to perform using standard tracking criteria. This study presents a novel tracking algorithm by integrating input estimation and modified probabilistic data association filter to solve this difficulty in a clear environment. The proposed algorithm with a new defined association probability in this filter provides a good tracking capability for the warhead ignoring the radar cross section. The simulation results indicate that the errors between the estimated and the warhead trajectories are reduced to a small interval in a short time. Therefore, the radar can produce a beam to illuminate to the right area and keep tracking the warhead all the way. In conclusion, this algorithm is worthy of further study and application.

• Journal of the Korea Institute of Military Science and Technology
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• 제22권3호
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• pp.401-407
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• 2019

In this paper, the position estimation considering wheel slip of mecanum wheeled mobile robots is discussed. Since the mecanum wheeled mobile robot does not need a space to rotate, it is very suitable in narrow industrial fields. However, the slip caused by the roller attached to the wheel makes it difficult to estimate the position precisely. Due to these limitations, mecanum wheels are rarely applied to unmanned mobile robots in automation factories. In this paper, a method to compensate the orientation and distance error caused by the slip is proposed. The exact orientation is measured by fusing gyro and magnetometer sensor data with application of Kalman filter. In addition, the kinematic model accounting slip effects will be defined to compensate the distance error.

• Proceedings of the KIPE Conference
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• 전력전자학회 2003년도 추계학술대회 논문집
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• pp.127-131
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• 2003

This paper describes an initial pole position estimation method of a magnetic pole sensorless permanent magnet synchronous motor(PMSM) with an incremental encoder, The accurate initial pole position is estimated by using an efficient numerical method of Secant Method, which finds either of two zero torque/force positions and then the correct d-axis. It can be simply applicable to both rotary and linear PMSM because it only requires the tuned current controller and the relative position information. The experimental results show the validity of the proposed method with respect to highly accurate pole position estimation under the moderate moving distance and convergence time.

• Korean Journal of Computational Design and Engineering
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• 제14권1호
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• Journal of Welding and Joining
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• 제29권6호
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• pp.82-87
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• 2011

In this study, we conducted laser welding by using remote scanner that is 5J32 aluminum alloy to observe the mechanical properties and optimize welding process parameters. As the control factors, laser incident angle, laser power and welding speed were set and as the result of weldablility, tensile shear tests were performed. ANOVA (Analysis of Variation) was also carried out to identify the influence of process variables on tensile shear strength. Strength estimation models were suggested using regression alnalysis and 2nd order polynomial model had the best estimation performance. In addition optimal welding condition was determined in terms with wedalility and productivity using objective function and fitness function. Final optimized welding condition was laser power was 4 kW, and welding speed was 4.6 m/min.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.214-221
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• 2016

An attitude estimation algorithm which integrates gyroscope and vision measurements using an adaptive complementary filter is proposed in this paper. In order to make the filter more tolerant to vision measurement fault and more robust to system dynamics, fuzzy interpolator is applied. For recognizing the dynamic condition of the system and vision measurement fault, the cut-off frequency of the complementary filter is determined adaptively by using the fuzzy logic with designed membership functions. The performance of the proposed algorithm is evaluated by experiments and it is confirmed that proposed algorithm works well in the static or dynamic condition.

• International Journal of Control, Automation, and Systems
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• 제3권3호
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• pp.486-492
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• 2005

A practical recursive WLS (weighted least squares) algorithm is proposed to estimate relative range using LOS (line-of-sight) information for ASM (anti-ship missile) application. Apart from the previous approaches based on the EKF (extended Kalman filter), to ensure good convergence properties in long range engagement situations, the proposed scheme utilizes LOS rate measurements instead of conventionally used LOS angle measurements. The estimation error property for the proposed filter is investigated and a simple error compensator is devised to enhance its estimation error performances. Simulation results indicate that the proposed filter produces very accurate range estimates with extremely small computations.

• Journal of Biomedical Engineering Research
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• 제6권1호
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• pp.1-4
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• 1985

Background EEG signals can be represented as the sum of a conventional AR process and an innovation process. It is know that conventional estimation techniques, such as least square estimates (LSE) or Gauasian maximum likelihood estimates (MLE-G) are optimal when the innovation process satisfies the Gaussian or presumed distribution. When the data are contaminated by outliers, however, these assumptions are not met and the power spectrum estimated by conventional estimation techniques may be fatally biased. EEG signal may be affected by artifacts, which are outliers in the statistical term. So the robust filtering estimation technique is used against those artifacts and it performs well for the contaminated EEG signal.