• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.119-127
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• 1999

In this paper, a robust direct adaptive contrdler is presented in a linear time-invariant. Continuous systems with unmodeded dynamics and bounded disturbance using a rmdified control law and the adaptive law to Compensate for the drawback of ${\sigma}$-modification algorithm. The proposed algorithm is awlied to a plant with unrmdeled dynamics represented as a singular perturbation. Boundness of all signals in overall system is guaranteed with mathematical analysis. simulation results are presented the effectiveness foc the first-order plant even in the presence of unmodelled dynamics or bounded disturbance simulatneousIy.eousIy.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.2
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• pp.109-114
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• 2001

본 논문에서는 비선형 제어시스템의 성능 개선을 위한 새로운 신경망 직접 적응제어 알고리즘을 제시하였다. 제어칙은 Gaussian RBF 신경망을 이용한 제어입력과 근사화 오차 및 외란의 영향을 제거하기 위한 보조제어 입력으로 구성하였다. 또한 신경망에 사용된 가중치와 보조입력의 파라미터를 조정하기 위한 적응칙은 Lyapunov 안정도 이론에 의하여 구하였다. 이렇게 함으로써 외란이나 근사화 오차에 관계없이 플랜트와 기준모델 사이의 오차가 0이 되도록 하는 알고리즘을 구할 수 있었다. 또한 제시된 알고리즘의 효용성을 알아보기 위하여 Duffing forced oscillation 시스템에 대하여 시뮬레이션 하여본 결과 만족할만한 성능을 얻을 수 있었다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.11
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• pp.394-403
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• 1983

This paper discusses a model reference adaptive control for a multi-input multi-output continuos system in matrix fraction description. The controller is of Monopoli-Narendra type with a time-varying gain matrix in the parameter adaptation law. The transfer matrix of the given plant with an adjustable controller is made to approach to that of the reference model asymptotically. It is shown that, under some plausible assumptions such as on the knowlidge of an interactor matrix, the algorithm for a single-input single-output system can be appropriately extended to a multi-input multi-output system. The convergence of an adaptation law is estavlished with some stability theory and stability of the overall system is asserted by an analytical investigation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.603-610
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• 2000

In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.5
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• pp.83-93
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• 1996

In this paper, a minimum variance control system is proposed and practically implemented, which is adequate to the induction motor speed control system with frequent load variation. Minimum variance control method is used as a control law and recursive least square method with selective forgetting factor is proposed and analyzed with general forgetting algorithm as an estimation method. Designed control system is based on PC-DSP structure for the purposed of easiness of applying adaptive algorithm. Through computer simulation and experimental results, it is verified that proposed control system is robust to the load variation and practical implementation is possible.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.31-37
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• 2001

A robust adaptive technique for the longitudinal control of a platoon of automated vehicles is presented. A nonlinear model is used to represent the dynamics of each vehicle within the platoon. The external disturbances such as wind gust and a disturbance term due to engine transmission variations and so on are considered. The state observer is used to avoid direct measurement of the relative velocity or acceleration between the controlled and leading vehicles or the controlled vehicles's acceleration. The proposed controller guarantees to recover platoon stability in operation even if a speed dependent spacing policy is adopted, which incorporates a constant time headway in addition to the constant distance. It is shown that the proposed observer is exponentially stable, and the at the robust adaptive controller is stable. The simulation results demonstrate excellent tracking even in the presence of disturbances.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.332-338
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• 2000

In this paper, a robust nonlinear excitation controller is proposed to achieve both voltage regulation and system stability enhancement for single machine-infinite power systems. The proposed method employs backstepping technique and combines this with an adaptation algorithm for estimating the effective reactance of transmission line, thereby leading to adaptive nonlinear control. Simulation results show that power that angle stabilization as well as voltage regulation is achieved in a satisfactory manner, regardless of the system operating conditions and system structure.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.1-8
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• 2003

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method is used to estimate the vehicle parameters, mass, time constant, etc. The inter-vehicle spacing and its derivatives are estimated by using the sliding mode cascade observer introduced in this paper. It is shown that the proposed adaptive controller is uniformly ultimately bounded. It is also shown that the errors of the relative distance, the relative velocity and the relative acceleration asymptotically converge to zero. The simulation results are presented to investigate the effectiveness of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.3
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• pp.266-272
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• 2004

In this paper, an observer-based adaptive controller is proposed to control the longitudinal motion of vehicles. The standard gradient method will be used to estimate the vehicle parameters such as mass, time constant, etc. The nonlinear model between the driving force and the vehicle acceleration will be chosen to design the state observer for the vehicle velocity and acceleration. It will be shown that the proposed observer is exponentially stable, and that the adaptive controller proposed in this paper is stable by the Lyapunov function candidate. It will be proved that the errors of the relative distance, velocity and acceleration converge to zero asymptotically fast, and that the overall system is also asymptotically stable. The simulation results are presented to investigate the effectiveness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.151-157
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• 2000

The MRAC theory has proved to be one of the most popular algorithms in the field of adaptive control, particularly for practical application to devices such as an hydraulic servosystem of which parameters are unknown or varying during operation. For small sampling period, the discrete time system becomes a nonminimal phase system. The $\delta$-MRAC was introduced to obtain the control performance of nonminimal phase system, because the z-MRAC can not control the plant for small sampling period. In this paper, $\delta$-MRAC is applied to the control of an hydraulic servosystem which is composed of servovalve, hydraulic cylinder and inertia load.