• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.325-328
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• 2002

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation is studied from an input-output feedback linearization with adaptive algorithm. The $\pi$-model of induction motor is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. Simulation results are provided for illustration.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2188-2191
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• 2002

MIMO 비최소위상 시스템에 대한 입출력 선형화 제어에 대해서 새로운 접근 방식을 제안한다. 처음에 몇가지 조건 하에서 비선형 궤환과 상태 변환을 하고 또한 magnitude & time scaling을 해서 일반적인 비선형 시스템을 특이 섭동 시스템으로 변환할 수 있다는 것을 보였다. 특히 제안된 방법에 의하여 변환된 특이 섭동 시스템에서 숨겨진 동적 특성이 fast subsystem의 역할을 하게 된다. 그 다음에는 잘 알려진 composite control 기법을 적용하여 시스템이 거의 선형적이고 비간섭적인 I/O 동적 특성을 갖게 하고 내부 상태가 안정화되도록 한다. 기존의 방식 보다 제안된 제어 방법의 가장 큰 이점은 적용될 수 있는 비최소위상 시스템의 범위를 보다 넓히게 되었다는 것이다. 게다가 특이 섭동 방법은 제어기 설계 과정을 단순화시켜 제어기 구현에 있어서 계산 시간을 단축시킨다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.185-188
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• 1997

In this paper, we execute identification, linearization, and control of a nonlinear system using recurrent neural networks. In general nonlinear control system become complex because of nonlinearity and uncertainty. And though we compose nonlinear control system based on the model, it is difficult to get good control ability. So we identify the nonlinear control system using the recurrent neural networks and execute feedback linearization of identified model, In this process we choose the optional linear system, and the system which will have to be feedback linearized if trained to follow the linearity between input and output of the system we choose. We the feedback linearized system by applying standard linear control strategy and simulation. And we evaluate the effectiveness by comparing the result which is linearized theoretically.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2355-2357
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• 2003

비선형성을 가지는 실제 플랜트의 제어기를 설계하기 위해서는 플랜트와 외부환경에 대한 충분한 정보를 필요로 한다. 그러나, 제어기 설계 시에는 실제 플랜트의 수학적 해석의 어려움, 모델링 오차와 외란 등의 원인으로 고려해야 할 복잡한 사항들이 있다. 이를 해결 하기 위한 기존 연구로는 플랜트에 대한 시스템 식별과 선형화를 통하여 공칭모델을 선정하고, 이를 제어하는 Model-based 방법과 모델이 아닌 실제 플랜트의 입출력 데이터를 토대로 제어기의 게인들을 반복 조절하는 Model-free 방법 등이 있다. 본 논문에서는 Model-free 방법 중에 하나인 반복 게인 조절 알고리즘을 기반으로 이 방법의 단점인 수렴속도지연을 보상하기 위한 목적으로 Model-based 방법 중에 하나인 외란 관측기(Disturbance Observer)를 결합한 새로운 제어 알고리즘을 제안하고, ODD(Optical Disk Drive)에서 사용되는 플 랜트에 적용한 모의 실험을 통하여 그 유용성을 보였다.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.578-581
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• 1996

A torque trajectory control of the IPM synchronous motor using an adaptive input-output linearization technique is proposed. The input-output linearization is performed using the estimated torque output with the knowledge of machine parameters. The linearized model gives the output torque error under the variation of the flux linkage. To give a good torque tracking in the presence of the flux linkage variation, the flux linkage will be estimated where the adaptation law h derived by the Popov's hyperstability theory and the positivity concept. This estimated value is also used for the generation of the d-axis current command for the maximum torque control. Thus, a good torque tracking and the exact maximum torque-per-current operation will be obtained.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.53-61
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• 1998

This paper describes the stability analysis of TSK (Takagi-Sugeno-Kang) fuzzy systems which can represent a large class of nonlinear systems with good accuracy. A TSK fuzzy model consists of TSK fuzzy rules and the consequent of each fuzzy rule is a linear input-output equation with a constant term. There may exist equilibrium points more than one in the TSK fuzzy model and each equilibrium point rnay also have different nature of stability. The local stability of an equilibrium point is determined by eigenvalues of the Jacobian matrix of the linearized TSK fuzzy model around the equilibrium point. Stability of both the continuous-time and the discrete-time systems is analyzed in this paper.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.2
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• pp.119-127
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• 2008

In this paper, the modular line-connected photovoltaic PCS (photovoltaic power conditioning system) is proposed. A step-up DC-DC converter using a active-clamp circuit and a dual series-resonant rectifier is proposed to achieve a high efficiency and a high input-output voltage ratio efficiently. An IncCond (incremental conductance) MPPT (maximum power point tracking) algorithm that improves MPPT characteristic is used. The PV module current is estimated without using a DC current sensor. By control a inverter using a linearized output current controller, a unity power factor is achieved. All algorithms and controllers are implemented on a single-chip microcontroller and the superiority of the proposed DC-DC converter and controllers is proved by experiments.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.24-33
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• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.

• Journal of IKEEE
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• v.9 no.1 s.16
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• pp.72-78
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• 2005

This paper describes the design of a robust output-feedback controller for a single-input single-output nonlinear dynamical system with a full relative degree. While all the previous research works on the output-feedback control are based on dynamic observers, a new state estimator which uses the past values of the measurable system output is proposed. We name it backward-difference state estimator since the derivatives of the output are estimated simply by backward difference of the present and past values of the output. The disturbance generated due to the error between the estimated and real state variables is compensated using an additional robustifying control law whose gain is tuned adaptively. Overall control system guarantees that the tracking error is asymptotically convergent and that all signals involved are uniformly bounded. Theoretical results are illustrated through a simulation example of inverted pendulum.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.907-914
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• 2004

In this paper, we present a reduced-order observer for a class of nonlinear systems based on the input output linearization. While the most results in the literature presented full-order nonlinear observer, we proposed a procedure for the design of reduced-order observer far nonlinear systems that are not necessarily observable. Assuming that there exists a global observer fer internal dynamics and that certain functions are globally Lipschitz, we can design a global reduced-order observer An illustrative example is included that demonstrate the design procedure of the proposed reduced-order observer.