• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.140-146
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• 1993

Active noise control uses the intentional superposition of acoustic waves to create a destructive interference pattern such that a reduction of the unwanted sound occurs. In active noise control system the choice of a control structure and design of the controller are the main issues of concern. In real acoustic fields there are a vast number of noise sources with time-varying nature and the characteristics of transducers and the geometric set-up of control system are subject to change. Accordingly the control system should be designed to adapt such circumstances so that required level of performance is maintained. In this paper, the adaptive control algorithm for self-tuning adaptive controller is presented for the application in active noise control system. Self-tuning is a direct integration of identification and controller design algorithm in such a manner that the two processes proceed sequentially. The least mean square algorithm was used for the identification schemes and adaptive weighted minimum variance control algorithm was applied for self-tuning controller. Computer simulation results for self-tuning feedback controller are presented. And simulation results was shown to be useful for the situation in which the periodic noise sources act on the acoustic field.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.6
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• pp.49-56
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• 1995

In this study, self-tuning adaptive control using state observer is developed. Self-tuning adaptive controller that estimates the parameters of the system in real time and generates the optimal control signals has robust characteristic about varying load and external disturbances. In addition, state observer without sensors is applied, thus the control can be performed more quickly and exactly. Since chopper is used commonly in practical drives, the characteristics of the chopper are included in state observer algorithm, which, in turn, makes the system exact estimation. Since series type DC motor has nonlinear models, linearizing approach are investigated. to realize the proposed algorithm it requires fast calculation in real time. TMS320C31, digital signal processor, is applied to realized the adaptive control algorithms.

• Journal of Sensor Science and Technology
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• v.6 no.2
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• pp.123-130
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• 1997

In this paper, we present an original stereo vision system which comprises two process: 1. An image segmentation algorithm based on new concept called declivity and using automatic thresholds. 2. A new stereo matching algorithm based on an optimal path search. This path is obtained by dynamic programming method which uses the threshold values calculated during the segmentation process. At present, a complete depth map of indoor scene only needs about 3 s on a Sun workstation IPX, and this time will be reduced to a few tenth of second on a specialised architecture based on several DSPs which is currently under consideration.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• Journal of KIISE
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• v.42 no.11
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• pp.1339-1348
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• 2015

In a distributed system environment based on a service-oriented architecture, separate systems collaborate to achieve the goals of the entire system by using services provided other systems. A service quality violation from using one service can cause runtime system failure in the environment. The existing self-adaptation methods follow fault tolerance mechanism that responds to a failure after a service quality violation. In other words, these methods are limited to responsive action. Therefore, a service-dependability-case based self-adaptation mechanism is necessary to preserve the dependability of the self-adaptive system. This paper demonstrates that the service-dependability-case based self-adaptation mechanism is better than QoS(quality of service)-based self-adaptation with fault tolerance to preserve the dependability of the self-adaptive system. Additionally, this paper suggests a method to present and analyze service dependability by using GSN(Goal Structuring Notation) which is the existing modeling method for the presentation of assurance cases, an action mechanism adapted using an analysis result of service-dependability-cases, a methods of leveraging the service-dependability-case based self-adaptation mechanism by following the service's life cycle, and the framework architecture including the major components and the interactions between the components in the control loop of the self-adaptation process.

• 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.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.3
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• pp.302-312
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• 2012

Underwater vehicles play a very important role in underwater engineering. Water-tight junction box (WJB) is one of the key components in underwater vehicle. This paper puts forward a pressure self-adaptive water-tight junction box (PSAWJB) which improves the reliability of the WJB significantly by solving the sealing and pressure problems in conventional WJB design. By redundancy design method, the pressure self-adaptive equalizer (PSAE) is designed in such a way that it consists of a piston pressure-adaptive compensator (PPAC) and a titanium film pressure-adaptive compensator (TFPAC). According to hydro-mechanical simulations, the operating volume of the PSAE is more than or equal to 11.6 % of the volume of WJB liquid system. Furthermore, the required operating volume of the PSAE also increases as the gas content of oil, hydrostatic pressure or temperature difference increases. The reliability of the PSAWJB is proved by hyperbaric chamber tests.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1691-1692
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• 2008

In this paper, the adaptive neural network technique is proposed to control the speed of wind power generation system. For maximizing generated power effectively, adaptive neural algorithm based on SRWMM(Self Recurrent Wavelet Neural Network) is derived to on-line adjust the excitation winding voltage of the generator. Through computer simulations, it is shown that the proposed method can achieve smooth and asymptotic rotor speed tracking.

• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.86-94
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• 2002

The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.54-60
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• 2005

In this Paper, an adaptive microphone array system with self-delay estimator is proposed. By showing that the adaptive blocking matrix (ABM) of the generalized sidelobe canceller (GSC) can estimate the relative time delay between each sensor, the proposed system utilizes the ABM not only for blocking target components in the blocked signal path, but also for estimating the relative time delay. Therefore, the proposed system requires only the GSC structure while maintaining the system performance similar to the conventional system using an additional time delay estimator as a preprocessor. Simulation results show that the performance of the proposed system is identical to the conventional system that uses an additional time delay estimation module.