• 전력전자학회논문지
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• 제15권6호
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• pp.425-431
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• 2010

본 논문에서는 표면부착형 영구자석 동기전동기의 속도 제어를 위하여 적응속도제어기를 제안한다. 제안된 적응 제어기는 모터 파라미터와 부하토크의 정확한 정보를 필요로 하지 않으므로 이들의 변동에 매우 둔감하다. 또한 제안된 제어시스템의 안정성을 해석적으로 증명한다. 본 연구에서 제안된 적응속도제어기의 성능을 검증하기 위하여, 모터 파라미터 및 부하토크 변동 하에서 시뮬레이션 및 실험 결과가 주어졌다. 본 결과를 통하여 제안된 속도제어기는 영구자석 동기전동기의 속도를 정확하게 제어할 수 있음을 검증하였다.

• 대한전기학회논문지
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• 제38권2호
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• pp.127-136
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• 1989

This paper describes the parameter convergence properties of an adaptive system to identify a single-input single-output plant model. It is demonstrated that, by using power spectrum analysis, the persistency of excitation (PE) condition in order to guarantee the exponential stability of the adaptive control system can be transformed into the positive definite behavior for the auto-correlation function matrix of adaptive signal. The existence of parameter nominal values can be analyzed by this condition and the convergence rates of parameter are determined by examining the auto-correlation function. We may use the sufficient richness (SR) of input spectrum instead of the PE condition to analyze the parameter boundedness. It can be shown that the eigen values of the auto-correlation function are always related with adaptive gain, input amplitude and positions or numbers of input spectra. In each case, the variation of parameter convergence rate can be also verified.

• 전자공학회논문지B
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• 제31B권3호
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• pp.39-46
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• 1994

In this paper, three types of parameter update law which can be used in model reference adaptive control are suggested based on speed-gradient algorithm which was introduced by Fradkov. It is shown that the parameter update law which was proposed by Narendra is a special from of these laws and that proposed parameter update laws can insure the global stability under some conditions such as attainability and convexity. We also comment that the transfer function of reference model shoud be positive real for the realization of parameter update law.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1172-1174
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• 2002

An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

• 한국지능시스템학회논문지
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• 제12권5호
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• pp.481-486
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• 2002

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-5) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control. Based on the derived design method, the parameter estimation for controllable canonical T-S fuzzy model is also Presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.264-267
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• 1988

One of the major reasons of Adaptive Control is to control time varying systems. In this paper new adaptive algorithms are suggested for a class of linear time varying systems that satisfy certain assumptions. These algorithms consist of three modules, modeling, parameter estimation and control. The key feature of this paper is that power series of time varying parameters are used for estimation.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 춘계학술대회 논문집
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• pp.131-136
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• 1997

This paper represent the variable structure adaptive mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in contiuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. the sampling process often forces the trajectory to oscillate in the neighborhood of the sliding surface. Adaptive control technique is particularly well-suited to robot manipulators where dynamic model is highly complex and may contain unknown parameters. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple sturcture is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control, Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• Transactions on Control, Automation and Systems Engineering
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• 제3권1호
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.32-35
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• 1987

An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonlinearties and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which combines the pole placement with the extended linearized perturbation model. And this control scheme has two components: a feadforward control and a feedback compensation control. Based on this, the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

• 한국정밀공학회지
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• 제12권8호
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• pp.140-146
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• 1995

In case the uncertainty existing in a system is assumed to satisfy the matching condition and to be come-bounded. Y. H. Chen proposed an adaptive robust control algorithm which introduced adaptive sheme for a design parameter into robust deterministic controls. In this paper, the adaptive robust control algorithm is applied to the position tracking control of direct drive robots, and simulation and experimental studies are conducted to evaluate control performance.