• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.113-118
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• 1996

Nonlinear Attitude Dynamic Equation for rigid-body satellite is derived and linearzed. Estimator using Kalman filter and controller are designed. Controller using LQR technique implemented on satellite under torque disturbance shows much better performance than those by using of Bang-Bang technique.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.357-365
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• 2011

This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.531-536
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• 1992

In GMA welding processes, monitoring and control of weld quality are extremely difficult problems. This paper describes a neural network-based method for monitoring and control of weld pool sizes. First, weld pool sizes are estimated via a neural estimator using multi-point surface temperatures, which are strongly related to the formation of weld pool, and then controlled using the estimated pool sizes. Two types of controllers using the pool size estimator are designed and tested. To evaluate the performance of the designed controllers, a series of simulation studies was performed.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.37-44
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• 2021

This study is implemented as a sensor-less position controller capable of multi-turn detection to replace the expensive absolute encoder used in the turret servo system. For sensor-less control, the position information of the rotor is essential. For this, a magnetic flux estimator was implemented from the mathematical model of IPMSM used in the turret servo system. The position of the rotor and the angular velocity of the rotor were obtained using the rotor magnetic flux calculated from the magnetic flux estimator. Using the zero-crossing technique, one pulse was generated for each rotation of the estimated rotor magnetic flux to measure the number of multi-turns. Simulation and experiment results confirmed the usefulness of the proposed method.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.26.4-27
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• 2008

The completion ('initiation' de facto) of the KASI Orbit Propagator and Estimator (KASIOPEA) has been delayed for several reasons unfortunately. Due to the lack of working staffs and the Division priority rearrangement, the initial plan was dismantled and ignored for many years. However, fundamental researches regarding the essential parts of KASIOPEA has been done by author. The numerical integration module of the KASIOPEA is the most sensitive part in the precision of the final output in general. There is no silver bullet in the numerical integration in an orbit propagation as a non-stiff ODE case. Many numerical integration method like single-step methods, multi-step method, and extrapolation methods have been used in overly populated orbit propagator or estimator. In this study, several popular methods from single-step, multi-step, and extrapolation methods have been tested in numerical accuracy and stability.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.135-141
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• 2008

A new approach to $H_{\infty}$ multi-step prediction is developed by applying the innovation analysis theory. Although the predictor is derived by resorting to state augmentation, nevertheless, it is completely different from the previous works with state augmentation. The augmented state here is considered just as a theoretical mathematic tool for deriving the estimator. A distributed algorithm for the Riccati equation of the augmented system is presented. By using the reorganized innovation analysis, calculation of the estimator does not require any augmentation. A numerical example demonstrates the effect in reducing computing burden.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1864-1876
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• 2015

In this paper, we propose a singular perturbation-like approach to EDFA gain controller design and analysis. Considering a three-level model of EDFA, a gain controller containing a state observer and a channel add/drop estimator is designed based on a singular perturbation - like concept. The proposed design methodology is shown to be effective and advantageous not only in theoretically verifying the asymptotic stability of systems with multi-time scales such as EDFA but also in designing an asymptotic estimator for channel add/drops which does not satisfy the matching condition.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.39-49
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• 2002

This paper presents a robust tracker design method that is specific to the trajectories of target aircraft. This method assumes that representative trajectories of the target aircraft are available. The exact trajectories known to the tracker enables the incorporation of the exact data in the tracker design instead of the measurement data. An estimator is designed to have acceptable performance in tracking a finite number of different target trajectories with a capability to trade off the mean and maximum errors between the exact trajectories and the estimated or predicted trajectories. Constant estimator gains that minimize the cost functions related to the estimation or prediction error are computed off-line from an iterative algorithm. This tracker design method is applied to the longitudinal motion tracking of target aircraft.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1045-1056
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• 2007

We consider M/M/1 feedback queues with multi-class customers. We assume that different classes of customers have different arrival rates, service rates and feedback probabilities. Using the h-transforms of McDonald(999) we derive an importance sampling estimator for an overflow probability that the total number of customers in the system reaches a high level before emptying.