• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.124-131
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• 1997

This paper presents a modified adaptive control scheme that improves the transient performance of the overall system while maintaining the asymptotic convergence of the output error. The proposed control scheme is characterized as the added outer dynamic feedback loop on the conventional adaptive control scheme. This control scheme enables various robust control methods that were developed for standard model reference adaptive controllers to be applied to the proposed controller. In contrast with the modified adaptive controllers that use augmented errors to provide additional dynamic feedback, the proposed controller uses tracking error directly, thereby reducing the tracking error significantly in the transient state and making the error insensitive to noise.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.343-348
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• 2007

This paper presents an adaptive controller for the compensation of state-dependent disturbance with unknown amplitude in a digital servo motor system. The state-dependent disturbance is caused by friction and eccentricity between the wheel axis and the motor driver of a mobile robot servo system. The proposed control scheme guarantees an asymptotical stability for both the velocity and position regulation. An experimental result shows the effectiveness of the adaptive disturbance compensator for wheeled-mobile robot in a low velocity diffusion tracking. A comparative experimental study with a simple PI controller is presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1478-1481
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• 2005

As the model of most practical system cannot be obtained, the practice of typical control method is limited. Accordingly, numerous artificial intelligence control methods have been used widely. Fuzzy control and neural network control have been an important point in the developing process of the field. This paper is proposed adaptive fuzzy-neural network based on the vector controlled interior permanent magnet synchronous motor drive system. The fuzzy-neural network is first utilized for the speed control. A model reference adaptive scheme is then proposed in which the adaptation mechanism is executed using fuzzy-neural network. Also, this paper is proposed estimation of speed of interior permanent magnet synchronous motor using artificial neural network controller. The back-propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back-propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2120-2125
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• 2005

The principal idea of vibration isolation is to filter out the response of the system over the corner frequency. The isolation objectives are to transmit the attitude control torque within the bandwidth of the attitude control system and to filter all the high frequency components coming from vibration equipment above the bandwidth. However, when a reaction wheels or control momentum gyros control spacecraft attitude, vibration inevitably occurs and degrades the performance of sensitive devices. Therefore, vibration should be controlled or isolated for missions such as Earth observing, broadcasting and telecommunication between antenna and ground stations. For space applications, technicians designing controller have to consider a periodic vibration and disturbance to ensure system performance and robustness completing various missions. In general, past research isolating vibration commonly used 6 degree order freedom isolators such as Stewart and Mallock platforms. In this study, the vibration isolation device has 3 degree order freedom, one translational and two rotational motions. The origin of the coordinate is located at the center-of-gravity of the upper plane. In this paper, adaptive notch filter finds the disturbance frequency and the reference signal in filtered-x least mean square is generated by the notch frequency. The design parameters of the notch filter are updated continuously using recursive least square algorithm. Therefore, the adaptive filtered-x least mean square algorithm is applied to the vibration suppressing experiment without reference sensor. This paper shows the experimental results of an active vibration control using an adaptive filtered-x least mean squares algorithm.

• 대한전자공학회논문지TE
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• 제39권4호
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• pp.414-422
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• 2002

본 논문에서는 적응 제어 문제를 다루기 위해 CFCM 클러스터링과 퍼지 균등화 기법을 이용하여 새로운 적응 뉴로-퍼지 제어기를 설계하고자 한다. 먼저 오프라인에서 CFCM은 입력데이터의 성질과 출력 패턴의 성질까지도 고려한 퍼지 클러스터링 기법으로 적응 뉴로-퍼지 제어기의 구조동정을 수행한다. 파라미터 동정은 역전과 알고리즘과 RLSE(Recursive Least Square Estimate)을 이용한 하이브리드 학습을 수행한다. 온라인 학습에서는 시변특성으로 인해 전제부 및 결론부 파라미터를 실시간으로 계산된다. 시뮬레이션으로 온 라인 적응 뉴로-퍼지 제어 시스템의 성능을 입증하기 위해 목욕물 온도제어 시스템에 대해 다루고 전형적인 퍼지 제어기에 비해 오프 라인과 온 라인 설계 모두 좋은 성능을 보이고자 한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.117-123
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• 2000

A new control method for precision robust position control of a PMSM (Permanent Magnet Synchronous Motor) using asymptotically stable adaptive load torque observer is presented in the paper. Precision position control is obtained for the PMSM system approximately linearized using the field-orientation method. Recently, many of these drive systems use the PMSM to avoid backlashes. However, the disadvantages of the motor are high cost and complex control because of nonlinear characteristics. Also, the load torque disturbance directly affects the motor shaft. The application of the load torque observer is published in [1] using fixed gain. However, the motor flux linkage is not exactly known for a load torque observer. There is the problem of uncertainty to obtain very high precision position control. Therefore, a model reference adaptive observer is considered to overcome the problem of unknown parameter and torque disturbance in this paper. The system stability analysis is carried out using Lyapunov stability theorem. As a result, asymptotically stable observer gain can be obtained without affecting the overall system response. The load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent current which gives fast response. The experimental results are presented in the paper using DSP TMS320c31.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1924-1929
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• 1991

The conventional sliding mode control and variable structure control (VSC) of nonlinear uncertain system are well known for their robust property and simplity of control law. However, the use of them is only pardonable on the assumption that the upper-bound of parameter variation or nonlinearity is known and that the complete information about state is available. Though the former has been solved with adaptive robust control theory recently, the latter seems not to be solved. In this paper, we try to solve this problem using the technique of VSS adaptive robust control theory. That is, we propose a VSS adaptive observer and a sliding mode control incorporated with this observer. We can prove the robust stability of the closed system applying the Lyapunov's second method.

• 전기전자학회논문지
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• 제13권1호
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• pp.36-40
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• 2009

시간지연 시스템 제어에서 시스템 모델과 외란에 대한 정보를 정확히 구할 수 있으면 스미스 예측제어기를 이용하여 이상적인 출력 특성을 얻을 수 있다. 따라서 본 논문에서는 모델링 오차 및 외란이 존재하는 시간지연 시스템을 효과적으로 제어할 수 있는 적응제어 알고리즘을 제시하였다. 이를 위하여 시스템 모델과 외란을 검출 할 수 있는 적응관측자 및 적응 알고리즘을 제안하였으며 이 신호들을 이용한 스미스 예측제어기를 구성하였다. 그 결과 모델링 오차 및 외란의 영향을 소거할 수 있는 제어기를 설계 할 수 있었다. 이렇게 구성된 제어기에 대하여 컴퓨터 시뮬레이션을 행하여 제안된 시스템의 효용성 및 우수성을 입증하였다.

• Smart Structures and Systems
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• 제21권6호
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• pp.777-791
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• 2018

This paper discusses the shape control of deformable mirrors for Adaptive Optics in the dynamic range. The phenomenon of control-structure interaction appears when the mirror becomes large, lowering the natural frequencies $f_i$, and the control bandwidth $f_c$ increases to improve the performance, so that the condition $f_c{\ll}f_i$ is no longer satisfied. In this case, the control system tends to amplify the response of the flexible modes and the system may become unstable. The main parameters controlling the phenomenon are the frequency ratio $f_c/f_i$ and the structural damping ${\zeta}$. Robustness tests are developed which allow to evaluate a lower bound of the stability margin. Various passive and active strategies for damping augmentation are proposed and tested in simulation.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.95-105
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• 2001

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).