• 제어로봇시스템학회논문지
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• 제8권12호
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• pp.1004-1013
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• 2002

A multirate state feedback control (MRSFC) method is proposed for systems sensitive to disturbance and noise based on the multirate estimator design using current estimator. MRSFC updates the controller output slower than the measurement sampling fiequency of system output by a lifting factor $R=T_c/T_s$ The closed-loop MRSFC system is less sensitive to disturbance and noise due to filtering effect than the conventional single-rate control system The multirate estimator gain can be obtained by solving a conventional pole placement problem such that MRSFC has the same spectrum of eigenvalues in the s-plane as the single-rate control. We applied the proposed multirate state feedback controller to a galvanometer servo system Simulation and experimental results show that settling and tracking performances are improved compared with a conventional single-rate pole placement control (PPC).

• Nuclear Engineering and Technology
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• 제25권1호
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• pp.110-124
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• 1993

적응 비례-적분-추정 (PIF) gain 및 가변구조 제어기를 사용하는 비선형 모델에 의한 하이브리드 제어방법 (NHC)이 개발되었다. 이 제어기는 모델의 불확실성에 대해 robust한 성질을 가지며 단일 입-출력 비선형 시스템의 추적제어 (tracking control)에 응용된다. 이 방법의 특징은 제어기가 각각 특정 역할을 수행하는 4개 부분으로 구성되는 것이다. 즉, 적응 P-I-F 및 가변구조 제어기로 구성된다. Lyapunov의 제 2방법으로 결정된 적응 PIF gain에 의한 제어성능 확보 및 모델의 불확실도를 평가하여 피이드백 함으로써 모델의 불확실성에 대해 robust한 제어기를 구성하였다. 가변구조 제어기는 PIF gain이 적절히 결정되지 않은 상태인 초기의 오차증가를 제어하기 위해 도입되었다. 새로 개발된 NHC방법을 원자로의 출력변동 제어에 응용한 결과 기존의 모델을 이용한 제어방법 (model-based controller)들에 비해 제어성능이 크게 개선되었다.

• 한국융합학회논문지
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• 제5권4호
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• pp.163-169
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• 2014

A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.230-235
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• 1992

We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.267-270
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• 1995

In this paper, a variable structure control scheme with a terminal sliding mode is proposed for robot manipulators. The proposed control scheme guarantees that the output tracking error converges to zero in finite time, and the overall system shows robust property against parametric uncertainties and external disturbances all the time.

• International Journal of Aeronautical and Space Sciences
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• 제15권1호
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• pp.74-81
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• 2014

This article documents the design of a novel two-loop acceleration autopilot based on $\mathcal{L}_1$ adaptive output feedback control for tail-controlled missiles. The inner loop is an adaptive angle-of-attack tracking loop and the outer loop is the traditional PI controller for error compensation. A systematic low-pass filter design procedure is provided for minimum phase system and is applied to the inner loop design while the parameters of the outer loop are obtained from the multi-objective optimization problem. The effectiveness of the proposed autopilot is verified through numerical simulations under various conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1730-1731
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• 2007

In this paper, we present a direct adaptive control method using neural networks for the control of nonlinear systems. The weights of neural networks are trained by an adaptive backpropagation algorithm based on Lyapunov stability theory. We develop the parameter update-laws using the neural network input and the error between the desired output and the output of nonlinear plant to update the weights of a neural network in the sense that Lyapunove stability theory. Beside the output tracking error is asymptotically converged to zero.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.237-242
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• 2000

The areal recording density of HDD(Hard Disk Drive) has been increasing by about 60% a year. In order to achieve high areal density, less track pitch is expected and more servo bandwidth is required. Dual stage actuator and servo controller for HDD have been suggested for achieving high track density as a possible solution. Dual-loop servo system is generally classified into a two-input-two-output system, but if we use an estimator for a two-input-two-output system, it can be converted into two input one output system. Since we can't control the dual stage servo system by the classical method, it requires a special technique; for example, Parallel Loop System, Master-Slave Loop System, Decoupled Master-Slave Loop System, and Dual Feedback Loop System. In this paper, we performed experimental evaluations of several types of control algorithm. Further experiments will be made in the future.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.176-178
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• 2003

This paper presents a new velocity estimation strategy of a non-salient permanent magnet synchronous motor(PMSM) drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system which has the information of rotor position error. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error to aero. For zero and low speed operation, the PI gains of rotor position tracking controller have a variable structure. The PI tuning formulas are derived by analyzing this control system using the frequency domain specifications such as phase margin and bandwidth assignment.

• 전기학회논문지
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• 제67권2호
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• pp.216-223
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• 2018

Since solar cells have non-linear voltage-current output characteristics, Photovoltaic systems require the Maximum Power Point Tracking(MPPT) function. For this reason, a large number of MPPT techniques have been studied. However, the conventional MPPT techniques may fail to track the maximum power point when partial shading occurs in the solar cell array due to its characteristics. Therefore, it is necessary to research the MPPT technique that can follow the maximum power point in the partial shadow condition. In this paper, the characteristics of solar cell arrays in partial shadowing are analyzed and the MPPT technique which can follow the maximum power point in partial shadow condition has been proposed. To validate the proposed MPPT method, simulation and experimentation results are provided.