• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.905-912
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertainties are upper-bounded by a linear combination of unknown constants and known continuous functions. The state of the closed-loop system is proven to be ultimately bounded. The proposed method modifies the method of Corless and Leitmann in the following two respects. First, the linear region of the saturation function in controller is fixed. Second, the intergration from in parameter estimator is replaced by a low pass filter form. These modifications prevent performance degradation and destabilization of the control system more effectively. The norm of the system states can be made sufficiently small by an appropriate choice of design parameters in the control law. The applicability of the proposed scheme is demonstrated in the position control of a simple pendulum via simulation.

• Proceedings of the KIEE Conference
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• summer
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• pp.1245-1247
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• 2004

This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.160-167
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• 2007

In this paper, we presented the development results of high speed wavefront sensor which is used in diagnosing the beam quality of He-Ne laser for adaptive optics system. The beam quality information of laser in AO system is necessarily required for diagnosing the optical components or correcting the distorted wavefront afterward. According to system requirements, normally, it is requested that there are high precision of measurement and real time processing speed. The developed wavefront sensor in this paper achieved maximum 30Hz of measurement rate and ${\lambda}/20(\;{@}\;{\lambda}=0.6328{\mu}m)$ of measurement precision in RMS. We also applied the developed into an experimental adaptive system and verified the performance of it by correcting the aberrated wavefront with a rate of 30Hz and $\lambda$/20 precision using the combination of the developed and PID control algorithm.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.9
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• pp.808-816
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• 2016

In this paper, a new technique and cost function which can be to classify jamming signal and target signal from the spectral distribution of received signal in order to minimize the main beam distortion of target signal and to form nulls in the direction of jamming signal in array antennas of single port system is proposed. The proposed cost function is applied to the adaptive algorithm which has the fast convergence and stable nulling performance through the combination of the PSO(Particle Swam Optimization) algorithm and the gradient-based perturbation algorithm, which shows stable nulling performance adaptively even under the moving jamming signal where the incident direction of the jamming signal is changing with time.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.625-632
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• 2000

This paper proposes an adaptive multislot allocation algorithm in order to achieve large system capacity and higher throughput data transmissions. The proposed system is the combination of the slow adaptive modulation system, in which the base station dynamically a signs optimum modulation parameters measuring the CNR(carrier to noise power ratio) of each transmission terminal, and the multislot allocation scheme, in which the base station flexibly allocates an appropriate number of TDMA data slots according to the instantaneous load conditions. Computer simulations confirm that the proposed system can tremendously improve average message delay characteristics in comparison with the conventional fixed slot allocation method.

• Journal of Power Electronics
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• v.12 no.3
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• pp.468-476
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• 2012

The interior permanent magnet synchronous motor (IPMSM) has been widely used in electric vehicle applications due to its excellent power to weigh ratio. This paper proposes the maximum torque control of an IPMSM drive using an adaptive learning (AL) fuzzy neural network (FNN) and an artificial neural network (ANN). This control method is applicable over the entire speed range while taking into consideration the limits of the inverter's rated current and voltage. This maximum torque control is an executed control through an optimal d-axis current that is calculated according to the operating conditions. This paper proposes a novel technique for the high performance speed control of an IPMSM using AL-FNN and ANN. The AL-FNN is a control algorithm that is a combination of adaptive control and a FNN. This control algorithm has a powerful numerical processing capability and a high adaptability. In addition, this paper proposes the speed control of an IPMSM using an AL-FNN, the estimation of speed using an ANN and a maximum torque control using the optimal d-axis current according to the operating conditions. The proposed control algorithm is applied to an IPMSM drive system. This paper demonstrates the validity of the proposed algorithms through result analysis based on experiments under various operating conditions.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.817-818
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• 2006

In Magnetic Resonance Imaging(MRI), the QRS complex of ECG is used as a trigger signal for MRI scan. But, gradient and RF(radio frequency) artifacts which are caused to static and dynamic field in MRI scanner cause interference in the ECG. Also, the signal shape of theses artifacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false gating of the MRI. In case of using general FIR or IIR band-pass filters for minimizing the artifacts, artifact-reduction-ratio is not excellent. So, an adaptive real-time digital filter is proposed for reduction of noise by gradient and RF(radio frequency) artifacts. The proposed filter for MRI-Gating is based on the noise-canceller with NLMS(Normalized Least Mean Square) algorithm. The reference signals of the adaptive noise canceller are a combination of the noisy three channel ECG signals. In conclusions, the proposed method showed the acceptable quality of ECG signal with sufficient SNR for gating the MRI and possibility of real time implementation.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1146-1155
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• 2017

Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.859-867
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• 2004

To provide high-quality media streaming service over the best-effort Internet, a streaming methodology is required to response to the dynamic fluctuation of underlying networks. In this paper, we implement the MPEG-4 streaming system with adaptive transport based on priorities of media packets. The implemented system is composed of the common MPEG-4 streaming components such as elementary stream provider, sync and DMIF layer, and adaptive transport module including data prioritization and FEC control. More specifically, the prioritized sync layer packets (based on object level) are delivered to the transport module and then are encoded by an adaptive FEC encoder to help reliable transport. The FEC combination is dynamically adjusted by the feedback information from the receiver. In addition, low priority packets are selectively dropped to meet the limitation of available bandwidth. The experimental results over the emulation-based testbed show that the Proposed system can mitigate the impact of network fluctuation and thus improve the quality of streaming.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.895-896
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• 2008

We propose a adaptive combination of affine projection algorithm (APA) filters with different update interval. Two APA filters with different update interval are adapted independently in order to keep the advantages of both component filters. This novel scheme provides improvement of performance in term of the convergence rate and the steady-state error. Experimental results show good properties of the proposed algorithm.