• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.29-34
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• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.453-456
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• 1996

In this paper, the direct adaptive control using neural networks is presented for the control of chaotic nonlinear systems. The direct adaptive control method has an advantage that the additional system identification procedure is not necessary. In order to evaluate the performance of our controller design method, two direct adaptive control methods are applied to a Duffing's equation and a Lorenz equation which are continuous-time chaotic systems. Our simulation results show the effectiveness of the controllers.

• 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.

• 전기학회논문지P
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• 제53권4호
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• pp.201-204
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• 2004

In this paper, a direct adaptive tracking controller based Lyapunov method is designed for a wheeled mobile robots. A wheeled mobile robots have three degrees of freedom and two control variables. Therefore, it is difficult to control a mobile robot using the general linear control. We introduce two kinds of Lyapunov function for the design of the controller and verify the controller. A mobile robots using the designed adaptive direct tracking controller is well-behaved and is easily implemented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• 대한기계학회논문집A
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• 제24권12호
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• pp.2926-2934
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• 2000

This study presents a direct adaptive controller which is derived by using Lyapunovs direct methods for trajectory tracking control of a pneumatic cylinder. The structure of the controller is very simple and computationally efficient because it does not use either the dynamic model or the parameter values of the pneumatic system. The bounded stability of the system is shown in the presence of the bounded unmodeled dynamics. The bounded size of tracking errors can be made arbitrarily small without giving andy influences on either input or output variables. The trajectory tracking performance and the stability of the control system is verified experimentally. The results of the experiments show that the proposed controller tracks the given trajectories, sine function and cycloidal function trajectories, more accurately than PD controller does, and it stabilizes the system and adaptive variables.

• 한국통신학회논문지
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• 제17권10호
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• pp.1157-1163
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• 1992

비최소 위상 시스템에 대한 적응 제어 알고리즘의 발전은 제어 법칙에 있어서 발생되는 비정칙성(singularity)에 의하여 제한되어 왔다. 이러한 문제를 해결하기 위하여 직접 적응 제어방식과 간접 적응 제어방식을 사용하여 플랜트 신호에서의 영구 여기(persistency of excitation)를 유발시켜 플랜트의 실제값을 추정하기 위한 추정의 수렴성을 보장하는 방법과 간접 적응 제어방식을 사용하여 영구 여기 조건 없이 가제어성 필요 조건을 만족하도록 추정을 적절히 변형 시키는 방법이 연구되어 왔다. 본 논문에서는 직접 적응 제어방식을 사용하여 영구 여기 조건이 없어도 제어기의 파라메타 추정이 가능하도록 하였으며, 플랜트 파라메타의 추정없이 제어기의 파라메타를 직접 추정하도록하여 추정 알고리즘을 간소화하였다.

• 제어로봇시스템학회논문지
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• 제14권6호
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• pp.564-572
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• 2008

The performance of the direct adaptive time-delay command shaping filter depends on the select time-delay. In the previously introduced direct adaptive command shaping filter, however, the time-delay value is fixed and only the magnitudes of the impulses are learned. In this paper, the authors introduce a new scheme to adapt the time-delay which is to be used in conjunction with the direct adaptive command shaping for the improved vibration suppression in flexible motion system. In order to formulate the time-delay adaptation scheme, the authors have analyzed the effect of the time-delay value on the performance of the direct adaptive command shaping filter. By modifying the direct adaptation formula based on the analysis result the authors have established a set of equations to adapt the time-delay toward the optimal value. Simulation results show the effectiveness of the proposed time-delay adaptation approach for the improved vibration suppression.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.160-163
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• 1988

In this paper, the adaptive controller for the turret gun is discussed which uses model reference adaptive technique based on the Lyapunov direct method. Turret gun can be decomposed into two time-invariant SISO control systems. One is for the elevation angle control and the other is for the azimuth angle control under the assumption of independence each other. Thus we only consider here about the control loop for the elevation angle.