• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.928-934
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• 2002

A natural way to cope with fault tolerant control (FTC) problems is to modify the control parameters according to an online identification of the system parameters when a fault occurs. However. due to not only difficulties Inherent to the online multivariable identification in closed-loop systems, such as modeling errors, noise or the lack of excitation signals, but also long time requirement to identify the post-fault system and implemeutation of control problems during the identification process, we propose an alternative approach based on the observer-based fault detection and isolation (FDI) and model reference adaptive control (MRAC). The proposed robust fault diagnosis method is based on a bank of observers. We also propose a model reference adaptive control with changeable reference models according to the occurred faults. Simulation results of a flight control example show the validity and applicability of the proposed algorithms.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.322-325
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• 1994

Mareel and Bitmead proved the presence of chaotic signal in random noise by applying dead beat control theory to adaptive mechanism. In this paper robust adaptive theory is proposed. With the property of chaotic signal that has order and law, the proposed theory can enhance the control Performance by applying the recursive algorithm that uses dynamic relation which have small correlation. The performance of proposed algorithm is demonstrated with the computer simulation of position control of electric motor. In this simulation, the adaptive low is adopted to control electric motor and the Presence of chaotic signal in feedback signal is proved by using several method such as time series, fourier spectrum phase portrait method.

• Journal of KSNVE
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• v.7 no.3
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• pp.427-437
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• 1997

Mean active intensity based active control for the cancellation of radiated noise out of the duct exit is studied. The active intensity control strategy is drerived based on the relation of the exterior sound field out of the duct termination and interior sound field of the duct. One of the characteristics of this control strategy is that the control performance can be maintained regardless of the sensor loction, compared with the conventional local pressure control methods at either interior downstream or exterior field positions. It is also suggested that the digital filtering for the active intensity control can be achieved by time-domain filtered-x LMP (Lest-Mean-Product) adaptive algorithm. Experiments for an open-ended duct are performed to compare the active intensity control performance with conventional pressure control one. Active control experiment of local sound pressure is conducted by widely used filtered-x LMS adaptive Algorithm and active intensity control implementaion uses the derived filter d-x LMP algorithm. It is shown that the exterior sound fileds was much better observable by sensing of the active intensity than by just sound pressure. It is also demonstrated that the global control performance of external field by acoustic intensity is superior to the conventional sound pressure control performance.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2417-2419
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• 1998

In this paper, a new active noise control technique which combines a hybrid active noise control technique and a subband active noise control technique is presented. To reduce the computational burden the active noise control system, a weighted hybrid control technique is applied. This algorithm shows higher stability and good noise attenuation property in either broad band or narrow band active noise control systems in HVAC ducts. Computer simulations were performed to show the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.547-554
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• 2007

This thesis presents a kind of active noise control(ANC) algorithm for reducing noise due to engine inside a car. The proposed control algorithm is, by using WP(Wavelet Packet), a one improving the instability due to delay of noise transmission and the lack of response ability for the rapid change of noise, which are defects of the existing FXLMS(Filtered-X Least Mean Square) algorithm. The chief character of this system is a thing that faster operation than the FXLMS is implemented by inserting WP in the secondary path. In other words, WP implements parallel operation. Then, the weights of filter in the adaptive algorithm will be updated faster. In addition, because WP have so excellent a resolution, they can process very minute noise. The efficiency of this control algorithm will be demonstrated in the matlab simulation and in the actual experiments by using a Labview program and a car.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3195-3197
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• 2000

Narrowband active noise control (ANC) techniques to reduce the noise in thermal power plant are considered. To reduce the computational burden of the ANC system, an adjoint LMS algorithm instead of a filteredx LMS algorithm is used for adaptive filters. The square wave signal is used for the reference signal of adaptive filters to reduce the higher order harmonics as well as the fundamental frequency of noise. A computer simulation has done to show the effectiveness of a proposed algorithm.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.395-397
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• 2007

In this paper, a Gauss-Seidel fast affine projection (GS-FAP) algorithm developed for the linear active noise control (ANC) is further utilized for nonlinear ANC of a 2nd-order Volterra systems with a nonlinear primary path and a noisy secondary path. The simulation results, obtained by applying adaptive Volterra filtering, show that the proposed approach yields more stable and faster nonlinear AN.C, compared with the conventional methods for the nonlinear ANC in case of noisy plant models.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.81-84
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• 1998

For ANC systems applied to aircrafts or passenger ships, engines from which reference signals are usually measured are located so far from seats where main part of controllers are placed. It can make feedforward ANC scheme difficult to implement or very costly. Feedback ANC algorithms which do not require reference signals and use error signals alone to update the filter, are usually sensitive to measurement noise ' and impulse noise. In this paper, reference signal needed for the feedforward control is not measured directly but generated with the estimated frequencies. Cascade adaptive notch filter (ANF), which has the low computational burden, is used to implement ANC system in real time. Several ANFs of order 2 are connected in series to estimate multiple sinusoids. Computer simulations and experiments in the laboratory for verifying efficacy of the proposed algorithm are carried out.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.332-334
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• 1994

This paper proposes a robust active noise control (ANC) system. The system constructs filter with a standard model. An adaptive litter, connected to the system in parallel, compensates the modeling error. When the adaptive filter does not work, the proposed system is robust while the conventional system loses the noise control capability. But proposed ANC system shows that the performance is comparable with that of the conventional ANC system under normal conditions.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1368-1375
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• 2013

In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.