• Journal of applied mathematics & informatics
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• 제41권1호
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• pp.107-121
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• 2023

An epidemic infectious disease model consists of six compartments viz. Susceptible, Exposed, Infected, Quarantine, Recovered, and Virus with nonlinear saturation incidence rate is proposed to know the viral disease dynamics. There exist two biological equilibrium points for the model system. The system's local and global stability is done through Lyapunov's direct method about equilibrium points. The sensitivity analysis has been performed for the basic reproduction number and equilibrium points through the normalized forward sensitivity index. Sensitivity analysis shows that virus growth and quarantine rates are more sensitive parameters. In support of mathematical conclusions, numerical experimentation has been shown.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.898-901
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• 1988

Up to now, using adaptive control method, Identification deals with system whose entire state variables and prameters are accessible for measurement. In practical situations, all the state variables cannot be measured and it is impossible to directly apply since the parameters of the system are unknown. Therefore, in this paper, using only input-output data, such a model of the system is not available since the parameters of the system are unknown. this leads to the concept of an adptive observer in which both the parameters and the state variable of the system are identified simultaniously. Lyapunov's direct method and Kalman-Yakubovich (K-Y) lemma are employed to ensure the stability of this schemes. The feature is that the signal and adaptive gain which is generated from filter is imposed upon feedback vector and then state variables and the unknown parameters can be identified. To show the usefulness of the proposed schemes, computer simulation result of unknown second-order system shows the effectiveness of the proposed schems.

• 한국정밀공학회지
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• 제15권12호
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• pp.128-141
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• 1998

We propose the robust nonlinear controller design methodology for the multivariable system which has hard nonlinearities (Coulomb friction, dead-zone, etc) and the structured real parameter uncertainty. The hard nonlinearity can be linearized by the RIDF technique and structured real parameter uncertainty can be modelled as the sense of Peterson-Hollot's quadratic Lyapunov bound. For this system, we apply the robust QLQG/H$_{\infty}$ control and then can obtain four Riccati equations. Because of the system's nonlinearity, however, one Riccati equation contains the nonlinear correction term that is very difficult to solve numerically, In order to treat this problem, using some transformations to Riccati equations, the nonlinear correction term can be eliminated. Then, only two Riccati equations need to design a controller. Finally, the robust nonlinear controller is synthesized via IRIDF techniques. To test this proposed control method, we consider the direct-drive robot manipulator system that has Coulomb frictions and varying inertia.

• 전자공학회논문지CI
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• 제37권1호
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• pp.21-31
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• 2000

본 논문에서는 이산 시간 신경망 제어 시스템의 안정도에 대한 해석을 하도록 한다. 우선 리아프노프의 직접법을 이용하여 신경망제어기를 포함하고 있는 시스템의 안정조건을 체계적으로 유도하고 이 유도된 안정조건을 반영하여 수정된 역전파 알고리즘을 제안한다. 이 수정된 역전파 알고리즘은 유도된 신경망 제어기 시스템의 안정조건을 반영한 학습 규칙이고 따라서 이를 이용하여 학습된 신경망 제어기의 경우 안정성을 보장하게 된다. 끝으로 컴퓨터 모의 실험에서는 제안한 신경망 제어 시스템의 안정조건과 이를 반영한 수정 역전파 알고리즘을 통하여 주어진 플랜트를 학습 제어하도록 한다.

• 한국산업융합학회 논문집
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• 제18권3호
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• pp.139-149
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• 2015

In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.

• 한국지능시스템학회논문지
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• 제22권2호
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• pp.225-231
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• 2012

본 논문에서는 접근 각도 개념을 이용하여 과소작동기 형태의 무인 수중 잠수정의 경로 추적 제어기 설계 방법을 제안한 다. 과소 작동기 형태를 가지는 무인 수중 잠수정은 종 방향 추진력과 회전력에 의해 속도와 방향을 조절하나, 횡 방향 추 진기가 없기 때문에 횡 방향에 대한 움직임을 제어 할 수 없다. 이러한 무인 수중 잠수정의 과소 작동기 문제를 해결하기 위하여 본 논문에서는 기준 경로에 대한 접근 각도 개념을 제안하고, 제안한 접근 각도를 이용하여 경로 추적 제어기를 설 계한다. 이를 위해 동체 고정 좌표계에서 새로운 오차 방정식을 구하고, 리아푸노프 방법을 기반으로 경로 추적 제어기를 설계한다. 본 논문에서는 컴퓨터 시뮬레이션 통해 제안한 방법에 의해 설계된 제어기의 성능을 검증한다.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.414-427
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• 2006

This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.