• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.150-155
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• 2011

In an active noise control systems, an IIR filter may cause a problem in stability beacause of its poles. For IIR filter, its poles goes sometimes out of a unit circle in a z-plane in the transition state, where the adaptive algorithm converges to the optimum value, which causes the system to diverge. Fuzzy LMS algorithm has a better convergence property than conventional LMS algorithms, but is not applicable to IIR filter because of the reasons. Stabilized adaptive algorithm could be improves stability by moving the pole of IIR filer toward the origin forcibly in the transient state, and by introducing forgetting factor to maintain the optimum convergence when it reaches to the steady state. In this paper, We proposed stabilized adaptive fuzzy LMS algorithms with IIR filter structures, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3647-3653
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• 2012

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

• 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 D
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• v.55 no.8
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• pp.375-377
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.30-32
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• 2006

An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be Improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1332-1335
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• 1996

It is very important to predict the future position for the heavy vehicle with evasive maneuvering. In this paper, we considered for the manual image tracking system. The vehicle images are received from gyro stabilized mirror system, pass through the optical lens, processed, and displayed on the TV monitor. The operator try to lay the reticle to the center of vehicle image. When the vehicle is moving, the mirror platform (actually the line of sight) should follow the vehicle and the angular rate information is picked up from the mirror stabilized system. This rate signal should be used to predict the future vehicle position. The problem is that the visual system of the human operator is in the closed loop system. The rate signals are disturbed by the operator. In addition, there are some non linearities concerned with the control handle bar and the servo control system. The proposed Kalman filter, combined with some modifications for operator disturbance rejection, improved the predication of the future vehicle position when compared with the conventional passive filter used.

• Proceedings of the Optical Society of Korea Conference
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• 1998.08a
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• pp.166-167
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• 1998

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.3
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• pp.20-25
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• 1975

A microwave oscillator stabilized by a phase-locked loop (PLL) is developed. The PLL system is chosen 'compared with the cavity stabilized oscillator in view of the domestic manufacturing, because special machining and materials are needed for the latter. A sampler with a low pass filter is shown to be used as a phase detector in the PLL, and the sampler capable of sampling up to 4GHz is developed for this use. Frequency stability of about 10-6 is obtained from the developed microwave oscillator, operating at 2.16 GHz with more than 120 milliwatts output power, Ivhereby a crystal oscillator operating at about 110MHz is used as a reference source in the PLL. The capturing range of this oscillator is extended up to its lock-in-range of about 10MHz by employing a search oscillator in the system.

• Journal of the Korean Ceramic Society
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• v.24 no.5
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• pp.470-476
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• 1987

The system of 0.1Pb(Mg1/3N2/3)O3-yPbTiO3-zPbZrO3 piezoelectric ceramics was made in the radial model disk and ring dot type filter. The resonant frequency(fr) variations were investigated for 100 hours and the temperature range from 20$^{\circ}C$ to 100$^{\circ}C$. As the results, the morphotropic phase boundary was supposed to be the composition of 45 y 50 and 40 z 45. The best characteristic of againg effect, after 10-hours, was composed of y, z=45. The stabilized characteristic of temperature varition, to become 0.1% up to 100$^{\circ}C$, was composed of y=50 and z=40. The bandwidth was broadened with increasing the electromechanical coefficient(kp), and the filter characteristics was approached ideal mode with increasing mechanical quality factor(Qm). Kp and Qm affected combinationally on filter characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.241-245
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• 2005

Strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) yields reliable mission capability and enhanced navigational accuracy for spacecrafts. The theory and characteristics of integrated system based on unscented Kalman filtering is investigated in this paper. This Kalman filter structure uses unscented transform to approximate the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The filter implementation subsumed here is in a direct feedback mode. Axes misalignment angles of the SINS are observation to the filter. A simple approach for simulation of axes misalignment using stars observation is presented. The SINS error model required for the filtering algorithm is derived in space-stabilized mechanization. Simulation results of the integrated navigation system using a medium accuracy SINS demonstrates the validity of this method on improving the navigation system accuracy with the estimation and compensation for gyros drift, and the position and velocity errors that occur due to the axes misalignments.