• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.201-207
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• 2006

A robust Kalman filtering method for uncertain stochastic systems is suggested by adopting a perturbation estimation process which is to reconstruct total uncertainty with respect to the nominal state transition equation. The predictor and corrector of discrete Kalman filter are reformulated with the perturbation estimator. Successively, the state and perturbation estimation error dynamics and the corresponding error covariance propagation equations are derived as well. Finally we have the recursive algorithm of Combined Kalman Filter-Perturbation Estimator (CKF). The proposed combined Kalman filter-perturbation estimator has the property of integrating innovations and the adaptation capability to system uncertainties. A numerical example is shown to demonstrate the effectiveness of the proposed scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.110-114
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• 1995

This paper presents the on-board attitude determination algorithm for LEO (Low Earth Orbit) three-axis stabilized spacecraft. Two advanced star trackers and a three-axis Inertial Reference Unit (IRU) are assumed to be attitude sensors. The gyro in the IRU provides a direct measurement of the attitude rates. However, the attitude estimation error increases with time due to the gyro drift and noise. An update filter with measurements of star trackers and/or sun sensor is designed to update these gyro drift bias and to compensate the attitude error. Kalman Filter is adapted for the on-board update filter algorithm. Simulation results will be presented to investigate the attitude pointing performance.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.2
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• pp.63-68
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• 1999

This pper describes a digital sensorless drive of permanent magnet brushless DC motors. In order to detect in real time the rotor positions of which Emf becomes zero, terminal voltages are sampled during PWM duty cycle. This method generates detection error in indirect sensed position, which is the harmonic component of PWM frequency. In this paper, the drive adopted Butterworth low pass filter for rejection of the sensing error and for accurate estimation of commutation time. Analytical design process of the digital filter is proposed and the experimental results show that the performance of the proposed sensorless drive is superior to that of the sensorless drives without filterint.

• Journal of the Korea Computer Industry Society
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• v.8 no.2
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• pp.81-88
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• 2007

The dissertation which it sees in communication the noise . it will be able to occur confirms the effect which it gives to this videotex and it the Nagao filter it will be able to reduce a noise in one original videotex which is possible and nearly it analyzes the Nagao filter of existing compared to compared to a different divided territory and for the efficiency which restores it sets the filter which is the possibility of reducing the MSE (Mean Square Error) it proposes simulation and the result it leads and the superiority of this method it confirms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.929-936
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• 1991

An estimator for a discrete nonlinear system is derived in the sense of minimum mean square error. An optimal estimator for nonlinear system is very difficult to find and it will be infinite dimensional even if it is found. It has been known that the statistical linearization technique makes it possible to obtain a finite dimensional estimator. In this paper, the procedure of its derivation using the statistical linearization technique that gives an exact mean and variance information is introduced in the sense of minimum mean square error. The derived estimator cannot be clainmed to be globally optimal estimator because it uses the Gaussian assumption to the non-Gaussian distributed nonlinear output. However, the proposed filter exhibits a better performance compared to extended Kalman filter. Simulation results of a simple example present the improvement of the proposed filter in convergent property over the extended Kalman filter.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.620-623
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• 1997

This paper is concerned with the design of a suboptimal Kalman filter with robust state estimation performance for system models represented in the state space, which are subjected to parameter uncertainties in both the state and measurement matrices. Under the assumption that the uncertain system is quadratically stable, if the augmented system composed of the uncertain system and the filter is controllable, the proposed filter can provide the upper bound of the estimation error variance for all admissible uncertain parameters. This upper bound can be represented as the convex function of a parameter introduced in the design procedure, and the optimized upper bound of the estimation error variance can also be found via the optimization of this convex function.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.937-943
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• 2016

Vertical velocity is critical in many areas, such as the control of unmanned aerial vehicles, fall detection, and virtual reality. Conventionally, the integration of GPS (Global Positioning System) with an IMU (Inertial Measurement Unit) was popular for the estimation of vertical components. However, GPS cannot work well indoors and, more importantly, has low accuracy in the vertical direction. In order to overcome these issues, IMU-barometer integration has been suggested instead of IMU-GPS integration. This paper proposes a new complementary filter for the estimation of vertical velocity based on IMU-barometer integration. The proposed complementary filter is designed to minimize drift error in the estimated velocity by adding PID control in addition to a zero velocity update technique.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.217-218
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• 2006

We propose a method for improving the performance of the Amplitude Shift Keying (ASK) system using a fuzzy logic system for automatically tuning the bandwidth of low pass filter. Instead of a fixed bandwidth of a low pass filter of receiver, the fuzzy logic system is used to automatically adjust the bandwidth. The inputs to the fuzzy logic system are the error and change of error, and output is a bandwidth. Simulation results showed that the proposed system improves considerably on the performance of the fixed bandwidth.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.28-34
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• 1993

An algorithm for MMADF(modified multiplication-free adaptive filter) which need not to multiplication arithmatic operation is proposed to improve the performance of FSE (fractionally spaced equalizer) which reduce the ISI(intersymbol interference) in signal transfer channel. The input signals are quantized using DPCM and the reference signals is processed using a first-order linear prediction filter. The convergence properties of Sign. MADF and M-MADF algorithm for updating of the coefficients of a FIR digital filter of the fractionally spaced equalizer (FSE) are investigated and compared with one another. The convergence properties are characterized by the steady state error and the convergence speed. It is shown that the convergence speed of M-MADF is almost same as Sign algorithm and is faster than MADF in the condition of same steady state error. Especially it is very useful for high correlated signals.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.560-570
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• 1999

This paper formulates the suboptimal robust Kalman filtering problem into two coupled Linear Matrix Inequality (LMI) problems by applying Lyapunov theory to the augmented system which is composed of the state equation in the uncertain linear system and the estimation error dynamics. This formulations not only provide the sufficient conditions for the existence of the desired filter, but also construct the suboptimal robust Kalman filter. The proposed filter can guarantee the optimized upper bound of the estimation error variance for uncertain systems with parametric uncertainties in both the state and measurement matrices. In addition, this paper shows how the problem of finding the minimizing solution subject to Quadratic Matrix Inequality (QMI), which cannot be easily transformed into LMI using the usual Schur complement formula, can be successfully modified into a generic LMI problem.