• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.320-326
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• 2008

This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2459-2462
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• 2003

In this paper, we Propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently. We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.242-242
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• 2000

Comparing to the conventional adaptive filters using LMS algorithm, the proposed adaptive filters can reduce the amounts of computation and have robustness to variance of characteristics of input signals. LMS algorithm is performed in the domain of Hadamard transform after a reference signal and input signal are transformed by fast Hadamard transformation. As a transformation from time domain to Hadamard transformed domain, the proposed filter not only maintains the performance of estimating an input signal but also greatly reduces the number of multiplication. Moreover, the effect of characteristic changes of input signal is decreased. Computer simulation shows the stability and robustness of the proposed filter.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.349-349
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• 2000

A Clustering Adaptive Fuzzy Logic Controller(CAFLC) is applied to the torque control of a brushless do motor drive. Objective of this system includes elimination of torque ripple due to cogging at low speeds under loads. The CAFLC implemented has advantages of computational simplicity, and self-tuning characteristics. Simulation results showed that the torque ripple and dynamic response of the system using a CAFLC were superior to the model reference adaptive controlled system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.717-725
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• 2005

The adaptive filter is proposed for the INS/GPS. The proposed filter can estimate the variance of the process noise using the residual of the filter. To verify the efficiency of the adaptive filter, it is applied to the loosely-coupled INS/CPS that employs the additive quaternion error model. Simulation results demonstrate that the proposed filter is more effective in estimating the attitude error than EKF.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.341-344
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• 1993

This paper presents the general MRAC algorithm design, it's real time implementation and investigates the effect of purely deterministic disturbances to adaptive control algorithm. The design of adaptive control algorithm to reject the disturbances properly is also presented. In real time application, adaptive control algorithm is considered to investigate its performance by using DC motor. Disturbance rejection algorithm is investigated in simulation.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.452-455
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• 2003

Based on a field-oriented model of induction motor, adaptive backstepping approach using neural network(RBFN) is proposed for the control of induction motor in this paper. In order to achieve the speed regulation with the consideration of avoiding singularity and improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. rotor resistance uncertainty is compensated by adaptive backstepping and mechanical lumped uncertainty such as load torque disturbance, inertia moment, friction by RBFN. Simulation is provided to verify the effectiveness of the proposed approach.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.1
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• pp.19-29
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• 2019

This paper analyzes the design factors for GNSS anti-jamming receiver system in which the adaptive beamforming algorithm is applied in GNSS receiver system. The design analysis factors used in this paper are divided into three: antenna, beamforming algorithm, and operation environment. This paper analyzes the above three factors and presents numerical simulation results on antenna and beamforming algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.81-87
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• 2016

This paper analysis the AM-SCS-MMA (Adaptive Modulus-Soft Constraint Satisfaction-MMA) based on the adaptive modulus and minimus-disturbance technique in order to improve the stability and robustness in low signal to noise power of current MMA adaptive equalization algorithm. In AM-SCS-MMA, it updates the filter coefficient applying the adaptive modulus and minimum-disturbance technique of deterministic optimization problem instead of LMS or gradient descend algorithm for obtain the minimize the cost function of adaptive equalization. It is possible to improve the equalizer filter stability, robustness to the various noise characteristic and simultaneous reducing the intersymbol interference due to the amplitude and phase distortion occurred at channel. The computer simulation were performed for confirming the improved performance of SCS-MMA. For these, the output signal constellation of equalizer, residual isi, MSE, EMSE (Excess MSE) which means the channel traking capability and SER which means the robustness were applied. As a result of computer simulation, the AM-SCS-MMA have slow convergence time and less residual quantities after steady state, more good robustness in the poor signal to noise ratio, but poor in channel tracking capabilities was confirmed than MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.113-119
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• 2018

This paper relates the AM-NM-MMA algorithm which possible to adaptive equalization performance improvement using the adaptive modulus instead of fixed modulus in the NM-MMA algorithm. The NM-MMA emerged for the tradeoff the MMA and SE-MMA algorithm characteristics, the MMA provides the less residual values in the steady state and have a slow convergence rate, the SE-MMA provides the fast convergence rate and increae the risidual values in the steady state. But the fixed modulus can not give the zero residual values in the perfect equalization state and eqaulization performance were degrade, the adaptive modulus was applied in order to reducing the residual values, and its improved performance were confirmed by simulation. For this, the equalizer output constellation, residual isi, MD, MSE, SER were used for performance index. As a result of computer simulation, the AM-NM-MMA has more good performance in equalizer output signal constellation, residual isi, MD, MSE than the NM-MMA, but not in SER performance.