• Journal of Ocean Engineering and Technology
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• v.10 no.1
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• pp.108-118
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• 1996

This paper presents automatic reentry of a deepsea reser by adaptive control. Reentry is one of the major pro blems regarding a deepsea riser. In the reentry operation, the lower end of riser must be accurately positioned over the tarket point on the seabed. But the deepsea riser shows complex elastic response due to flexibility and nonlinearity of the riser dynamics and the required positioning accuracy is high. Moreover, elastic deformation must by controlled for securing structural integrity. In adaptive control, uncertainly known parameters like added mass and drag coefficient in the riser dynamics are identified and control forces at the floating body and the riser are calculated simultaneously. An Adaptive algorithm for MIMO linear discrete time system without requiring a persistent excitation is adopted in this study. The effectiveness of adaptive control logic is tested by numerical simulation and model experiment. The designed control system shows good overall performances, so that the present study can be applied to the control of the deepsea riser.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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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. TMS320C50 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 we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• Smart Structures and Systems
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• v.18 no.6
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• pp.1169-1188
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• 2016

Real-time substructuring techniques are currently an advanced experimental method for testing large size specimens in the laboratory. In dynamic substructuring, the whole tested system is split into two linked parts, the part of particular interest or nonlinearity, which is tested physically, and the remanding part which is tested numerically. To achieve near-perfect synchronization of the interface response between the physical specimen and the numerical model, a good controller is needed to compensate for transfer system dynamics, nonlinearities, uncertainties and time-varying parameters within the physical substructures. This paper presents the substructuring approach and control performance of the linear and the adaptive controllers for testing the dynamic characteristics of soil-structure-interaction system (SSI). This is difficult to emulate as an entire system in the laboratory because of the size and power supply limitations of the experimental facilities. A modified linear substructuring controller (MLSC) is proposed to replace the linear substructuring controller (LSC).The MLSC doesn't require the accurate mathematical model of the physical structure that is required by the LSC. The effects of parameter identification errors of physical structure and the shaking table on the control performance of the MLSC are analysed. An adaptive controller was designed to compensate for the errors from the simplification of the physical model in the MLSC, and from parameter identification errors. Comparative simulation and experimental tests were then performed to evaluate the performance of the MLSC and the adaptive controller.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.169-177
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• 2020

Malware analysis is one of the important concerns of computer security, and advances in analysis techniques have become important for computer security. In the past, the signature-based method was used to detect malware. However, as the percentage of packed malware increased, it became more difficult to detect using the conventional method. In this paper, we propose a method for identifying packers of packed programs using machine learning. The proposed method parses the packed program to extract specific PE information that can identify the packer and identifies the packer using the Adaptive Boosting algorithm among the machine learning models. To verify the accuracy of the proposed method, we collected and tested 391 programs packed with 12 types of packers and found that the packers were identified with an accuracy of about 99.2%. In addition, we presented the results of identification using PEiD, a signature-based PE identification tool, and existing machine learning method. The proposed method shows better performance in terms of accuracy and speed in identifying packers than existing methods.

• Environmental Mutagens and Carcinogens
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• v.21 no.2
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• pp.142-148
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• 2001

We studied adaptive response in CHL cells by benzidine dihydrochloride, a derivative of benzidine, which was a major mutagenic agent in dye industry. Chromosome aberration analysis was used for the identification of adaptive response to this mutagen. Adaptive and reactive doses were confirmed by cell proliferation rate curve. Cell proliferation rate curve was obtained from the mitotic indices of cells treated with various concentrations of benzidine dihydrochloride for 24 hours. Marked adaptive responses to benzidine dihydrochloride in the induction of chromosome aberration were observed in CHL cells by pre-treatment with low concentrations of benzidine dihydrochloride (0.0047 mg/$m\ell$ or 0.0094 mg/$m\ell$) for 24 hours following post-treatment with high concentrations (0.0187, 0.0375, 0.075, 0.15 mg/$m\ell$) for 24 hours. These adaptive responses were found mostly in the type of chromatid breaks and chromatid exchanges. There is no difference in these results between two adaptive doses, 0.0047 mg/$m\ell$ and 0.0094 mg/$m\ell$. The amount of adaptive response, however, was dependent on post-treatment doses.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.3-9
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• 1998

Since the introduction of hands-free phone set and teleconferencing system, acoustic echo cancellation has been a challenge for engineers. Recently many researches have shown that the best solution for the acoustic echo compensation problem is represented by an adaptive filter which iteratively tries to identify the unknown impulse response of the system from loudspeaker to microphone. In this paper, we apply the delayless subband adaptive filters and fast affine projection algorithm for the identification of room impulse response. Simulation results show 3∼8 dB more enhanced performance than conventional fullband adaptive filters or subband adaptive filters. In addition, fast affine projection algorithm shows better convergence speed at the expense of the low computational complexity than conventional LMS algorithm.

• Journal of KSNVE
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• v.5 no.3
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• pp.385-394
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• 1995

Recently, since robot manipulator becomes faster and lighter, its link is no longer regarded as rigid body, and robot controller which only controls robot position cannot reduce vibration of the flexible link. Therefore vibration control is needed in robot manipulator control in addition to position control. In the case that tip mass changes when robot manipulator in working, it is clear that the efficiency of the vibration/position controller designed for the fixed system goes down. In this paper, the system with time varying parameters, adaptive control theory is adopted which estimates parameters changed by the variation of the tip mass and re-calculates the gain of the controller. Validify of the proposed adaptive controller and capability of the estimator are evaluated by computer simulations and experiments. Comparison results of the optimal controller for the fixed system and proposed adaptive controller and carried out.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.540-545
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• 1988

In this study a microcomputer-aided design program has been developed to design and analysis for the digital adaptive control system. DACS(Digital Adaptive Control System) program has been written in GWBASIC language which is suitable for IBM-PC compatible. The dynamics of each element was modulized and described by linear difference equations. By the aid of this program, sampling time, the number of bits of A/D and D/A converter and the stability for the digital adaptive control system can be determined. In order to estimate the system parameters an on-line identification and a regression analysis method are utilized. The simulation results have been well agreed with the experiments. To demonstrate the utility of this program, an adaptive control system has been designed for air-heating system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.366-366
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• 2000

In this paper, an adaptive neuro-fuzzy filter using the conditional fuzzy c-means(CFCM) methods is proposed. Usualy, the number of fuzzy rules exponentially increases by applying the grid partitioning of the input space, in conventional adaptive neuro-fuzzy inference system(ANFIS) approaches. In order to solve this problem, CFCM method is adopted to render the clusters which represent the given input and output data. Parameter identification is performed by hybrid learning using back-propagation algorithm and total least square(TLS) method. Finally, we applied the proposed method to the nonlinear channel equalization problem and obtained a better performance than previous works.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.109-117
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• 1999

In this paper, a direct adaptive control, based on Lyapunov Function Candidate, is applied to a nonlinear Gunner's Primary Stabilized Head Mirror system to derive a parameter adaptation scheme; furthemore, a nonlinear sliding mode control, but also compensating the error in identification of the parameters which are even varying of have uncertain values. The performance of the adaptive controller is determined by the tracking ability to a desired model under some disturbances and the slowly varying parameters of the system. Both adaptive scheme and sliding mode play an important fole in the improvement of the nonlinear system control.